2020 |
Gregory Eady, Jonathan Nagler, Richard Bonneau, Joshua Tucker News Sharing on Social Media: Mapping the Ideology of News Media Content, Citizens, and Politicians Journal Article 2020. Abstract | Links | Tags: Social Media @article{Tucker2020d, title = {News Sharing on Social Media: Mapping the Ideology of News Media Content, Citizens, and Politicians}, author = {Gregory Eady, Jonathan Nagler, Richard Bonneau, Joshua Tucker}, url = {https://osf.io/ch8gj/}, doi = {https://doi.org/10.31219/osf.io/ch8gj}, year = {2020}, date = {2020-11-10}, abstract = {This article examines the news sharing behavior of politicians and ordinary users by mapping the ideological sharing space of political information on social media. As data, we use the near-universal currency of online political information exchange: URLs (i.e. web links). We introduce a methodological approach (and statistical software) that unifies the measurement of political ideology online, using social media sharing data to jointly estimate the ideology of: (1) politicians; (2) social media users, and (3) the news sources that they share online. Second, we validate the measure by comparing it to well-known measures of roll call voting behavior for members of congress. Third, we show empirically that legislators who represent less competitive districts are more likely to share politically polarizing news than legislators with similar voting records in more competitive districts. Finally, we demonstrate that it is nevertheless not politicians, but ordinary users who share the most ideologically extreme content and contribute most to the polarized online news-sharing ecosystem. Our approach opens up many avenues for research into the communication strategies of elites, citizens, and other actors who seek to influence political behavior and sway public opinion by sharing political information online.}, keywords = {Social Media}, pubstate = {published}, tppubtype = {article} } This article examines the news sharing behavior of politicians and ordinary users by mapping the ideological sharing space of political information on social media. As data, we use the near-universal currency of online political information exchange: URLs (i.e. web links). We introduce a methodological approach (and statistical software) that unifies the measurement of political ideology online, using social media sharing data to jointly estimate the ideology of: (1) politicians; (2) social media users, and (3) the news sources that they share online. Second, we validate the measure by comparing it to well-known measures of roll call voting behavior for members of congress. Third, we show empirically that legislators who represent less competitive districts are more likely to share politically polarizing news than legislators with similar voting records in more competitive districts. Finally, we demonstrate that it is nevertheless not politicians, but ordinary users who share the most ideologically extreme content and contribute most to the polarized online news-sharing ecosystem. Our approach opens up many avenues for research into the communication strategies of elites, citizens, and other actors who seek to influence political behavior and sway public opinion by sharing political information online. |
Finkel, E.J., Bail, C.A., Cikara, M., Ditto, P.H., Iyengar, S., Klar, S., Mason, L., McGrath, M.C., Nyhan, B., Rand, D.G., Skitka, L.J., Tucker, JA., et a. Political sectarianism in America Journal Article Science, 2020. @article{Tucker2020, title = {Political sectarianism in America}, author = {Finkel, E.J., Bail, C.A., Cikara, M., Ditto, P.H., Iyengar, S., Klar, S., Mason, L., McGrath, M.C., Nyhan, B., Rand, D.G., Skitka, L.J., Tucker, JA., et a.}, url = {https://science.sciencemag.org/content/370/6516/533/tab-article-info}, doi = {https://doi.org/10.1126/science.abe1715}, year = {2020}, date = {2020-10-30}, journal = {Science}, keywords = {USA}, pubstate = {published}, tppubtype = {article} } |
Nathaniel Persily, Joshua A. Tucker (Ed.) Social Media and Democracy: The State of the Field, Prospects for Reform Journal Article Cambridge University Press, 2020. Links | Tags: democracy, Social Media @article{Persily2020, title = {Social Media and Democracy: The State of the Field, Prospects for Reform}, editor = {Nathaniel Persily, Joshua A. Tucker}, url = {https://www.cambridge.org/core/books/social-media-and-democracy/E79E2BBF03C18C3A56A5CC393698F117}, doi = {https://doi.org/10.1017/9781108890960}, year = {2020}, date = {2020-08-20}, journal = {Cambridge University Press}, keywords = {democracy, Social Media}, pubstate = {published}, tppubtype = {article} } |
Meysam Alizadeh1, Jacob N. Shapiro, Cody Buntain, Joshua A. Tucker Content-based features predict social media influence operations Journal Article Science Advances, 2020. Abstract | Links | Tags: Social Media @article{Tucker2020c, title = {Content-based features predict social media influence operations}, author = {Meysam Alizadeh1, Jacob N. Shapiro, Cody Buntain and Joshua A. Tucker}, url = {https://advances.sciencemag.org/content/6/30/eabb5824}, doi = {https://doi.org/10.1126/sciadv.abb5824}, year = {2020}, date = {2020-07-22}, journal = {Science Advances}, abstract = {We study how easy it is to distinguish influence operations from organic social media activity by assessing the performance of a platform-agnostic machine learning approach. Our method uses public activity to detect content that is part of coordinated influence operations based on human-interpretable features derived solely from content. We test this method on publicly available Twitter data on Chinese, Russian, and Venezuelan troll activity targeting the United States, as well as the Reddit dataset of Russian influence efforts. To assess how well content-based features distinguish these influence operations from random samples of general and political American users, we train and test classifiers on a monthly basis for each campaign across five prediction tasks. Content-based features perform well across period, country, platform, and prediction task. Industrialized production of influence campaign content leaves a distinctive signal in user-generated content that allows tracking of campaigns from month to month and across different accounts. }, keywords = {Social Media}, pubstate = {published}, tppubtype = {article} } We study how easy it is to distinguish influence operations from organic social media activity by assessing the performance of a platform-agnostic machine learning approach. Our method uses public activity to detect content that is part of coordinated influence operations based on human-interpretable features derived solely from content. We test this method on publicly available Twitter data on Chinese, Russian, and Venezuelan troll activity targeting the United States, as well as the Reddit dataset of Russian influence efforts. To assess how well content-based features distinguish these influence operations from random samples of general and political American users, we train and test classifiers on a monthly basis for each campaign across five prediction tasks. Content-based features perform well across period, country, platform, and prediction task. Industrialized production of influence campaign content leaves a distinctive signal in user-generated content that allows tracking of campaigns from month to month and across different accounts. |
Pablo Barberá, Amber E Boydsun, Suzanna Linn, Ryan McMahon, Jonathan Nagler Automated Text Classification of News Articles: A Practical Guide Journal Article Political Analysis, 2020. Abstract | Links | Tags: Automated text analysis methods, Automated Text Classification, News, Practical Guide @article{Barbera2020, title = {Automated Text Classification of News Articles: A Practical Guide}, author = {Pablo Barberá and Amber E Boydsun and Suzanna Linn and Ryan McMahon and Jonathan Nagler}, url = {https://scholarsphere.psu.edu/concern/generic_works/dnc580n024}, doi = {https://doi.org/10.1017/pan.2020.8}, year = {2020}, date = {2020-06-09}, journal = {Political Analysis}, abstract = {Automated text analysis methods have made possible the classification of large corpora of text by measures such as topic and tone. Here, we provide a guide to help researchers navigate the consequential decisions they need to make before any measure can be produced from the text. We consider, both theoretically and empirically, the effects of such choices using as a running example efforts to measure the tone of New York Times coverage of the economy. We show that two reasonable approaches to corpus selection yield radically different corpora and we advocate for the use of keyword searches rather than pre-defined subject categories provided by news archives. We demonstrate the benefits of coding using article-segments instead of sentences as units of analysis. We show that, given a fixed number of codings, it is better to increase the number of unique documents coded rather than the number of coders for each document. Finally, we find that supervised machine learning algorithms outperform dictionaries on a number of criteria. Overall, we intend this guide to serve as a reminder to analysts that thoughtfulness and human validation are key to text-as data methods, particularly in an age when it is all-too-easy to computationally classify texts without attending to the methodological choices therein.}, keywords = {Automated text analysis methods, Automated Text Classification, News, Practical Guide}, pubstate = {published}, tppubtype = {article} } Automated text analysis methods have made possible the classification of large corpora of text by measures such as topic and tone. Here, we provide a guide to help researchers navigate the consequential decisions they need to make before any measure can be produced from the text. We consider, both theoretically and empirically, the effects of such choices using as a running example efforts to measure the tone of New York Times coverage of the economy. We show that two reasonable approaches to corpus selection yield radically different corpora and we advocate for the use of keyword searches rather than pre-defined subject categories provided by news archives. We demonstrate the benefits of coding using article-segments instead of sentences as units of analysis. We show that, given a fixed number of codings, it is better to increase the number of unique documents coded rather than the number of coders for each document. Finally, we find that supervised machine learning algorithms outperform dictionaries on a number of criteria. Overall, we intend this guide to serve as a reminder to analysts that thoughtfulness and human validation are key to text-as data methods, particularly in an age when it is all-too-easy to computationally classify texts without attending to the methodological choices therein. |
Kevin Munger, Mario Luca, Jonathan Nagler, Joshua A Tucker The (Null) Effects of Clickbait Headlines on Polarization, Trust, and Learning Journal Article Public Opinion Quarterly, 2020. Abstract | Links | Tags: Clickbait, Digital Literacy, Experiments, Polarization, USA @article{Tucker2020, title = {The (Null) Effects of Clickbait Headlines on Polarization, Trust, and Learning}, author = {Kevin Munger and Mario Luca and Jonathan Nagler and Joshua A Tucker}, url = {https://academic.oup.com/poq/advance-article-abstract/doi/10.1093/poq/nfaa008/5827235?redirectedFrom=fulltext}, doi = {https://doi.org/10.1093/poq/nfaa008}, year = {2020}, date = {2020-04-30}, journal = {Public Opinion Quarterly}, abstract = {“Clickbait” headlines designed to entice people to click are frequently used by both legitimate and less-than-legitimate news sources. Contemporary clickbait headlines tend to use emotional partisan appeals, raising concerns about their impact on consumers of online news. This article reports the results of a pair of experiments with different sets of subject pools: one conducted using Facebook ads that explicitly target people with a high preference for clickbait, the other using a sample recruited from Amazon’s Mechanical Turk. We estimate subjects’ individual-level preference for clickbait, and randomly assign sets of subjects to read either clickbait or traditional headlines. Findings show that older people and non-Democrats have a higher “preference for clickbait,” but reading clickbait headlines does not drive affective polarization, information retention, or trust in media.}, keywords = {Clickbait, Digital Literacy, Experiments, Polarization, USA}, pubstate = {published}, tppubtype = {article} } “Clickbait” headlines designed to entice people to click are frequently used by both legitimate and less-than-legitimate news sources. Contemporary clickbait headlines tend to use emotional partisan appeals, raising concerns about their impact on consumers of online news. This article reports the results of a pair of experiments with different sets of subject pools: one conducted using Facebook ads that explicitly target people with a high preference for clickbait, the other using a sample recruited from Amazon’s Mechanical Turk. We estimate subjects’ individual-level preference for clickbait, and randomly assign sets of subjects to read either clickbait or traditional headlines. Findings show that older people and non-Democrats have a higher “preference for clickbait,” but reading clickbait headlines does not drive affective polarization, information retention, or trust in media. |
Van Bavel, J. J., Baicker, K., Boggio, P. S., Capraro, V., Cichocka, A., Cikara, M., Crockett, M. J., Crum, A. J., Douglas, K. M., Druckman, J. N. Drury, J., Dube, O., Ellemers, N., Finkel, E. J., Fowler, J. H., Gelfand, M., Han, S., Haslam, S. A., Jetten, J., Kitayama, S., Mobbs, D., Napper, L. E., Packer, D. J., Pennycook, G., Peters, E., Petty, R. E., Rand, D. G., Reicher, S. D., Schnall, S., Shariff, A., Skitka, L. J., Smith, S. S., Sunstein, C. R., Tabri, N., Tucker, J.A., van der Linden, S., Van Lange, P. A. M., Weeden, K. A., Wohl, M. J. A., Zaki, J., Zion, S. & Willer, R. Using social and behavioral science to support COVID-19 pandemic response Journal Article Nature Human Behavior, 2020. Abstract | Links | Tags: COVID-19 @article{Bavel2020, title = {Using social and behavioral science to support COVID-19 pandemic response}, author = {Van Bavel, J. J., Baicker, K., Boggio, P. S., Capraro, V., Cichocka, A., Cikara, M., Crockett, M. J., Crum, A. J., Douglas, K. M., Druckman, J. N. Drury, J., Dube, O., Ellemers, N., Finkel, E. J., Fowler, J. H., Gelfand, M., Han, S., Haslam, S. A., Jetten, J., Kitayama, S., Mobbs, D., Napper, L. E., Packer, D. J., Pennycook, G., Peters, E., Petty, R. E., Rand, D. G., Reicher, S. D., Schnall, S., Shariff, A., Skitka, L. J., Smith, S. S., Sunstein, C. R., Tabri, N., Tucker, J.A., van der Linden, S., Van Lange, P. A. M., Weeden, K. A., Wohl, M. J. A., Zaki, J., Zion, S. & Willer, R.}, url = {https://www.nature.com/articles/s41562-020-0884-z}, year = {2020}, date = {2020-04-30}, journal = {Nature Human Behavior}, abstract = {The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.}, keywords = {COVID-19}, pubstate = {published}, tppubtype = {article} } The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months. |
Yevgeniy Golovchenko, Cody Buntain, Gregory Eady, Megan A. Brown, Joshua A Tucker Cross-Platform State Propaganda: Russian Trolls on Twitter and YouTube during the 2016 U.S. Presidential Election Journal Article The International Journal of Press/Politics, 2020. Abstract | Links | Tags: Elections, Propaganda, Russia, Twitter, USA, YouTube @article{Golovchenko2020, title = {Cross-Platform State Propaganda: Russian Trolls on Twitter and YouTube during the 2016 U.S. Presidential Election}, author = {Yevgeniy Golovchenko and Cody Buntain and Gregory Eady and Megan A. Brown and Joshua A Tucker}, url = {https://doi.org/10.1177/1940161220912682}, year = {2020}, date = {2020-04-14}, journal = {The International Journal of Press/Politics}, abstract = {This paper investigates online propaganda strategies of the Internet Research Agency (IRA)—Russian “trolls”—during the 2016 U.S. presidential election. We assess claims that the IRA sought either to (1) support Donald Trump or (2) sow discord among the U.S. public by analyzing hyperlinks contained in 108,781 IRA tweets. Our results show that although IRA accounts promoted links to both sides of the ideological spectrum, “conservative” trolls were more active than “liberal” ones. The IRA also shared content across social media platforms, particularly YouTube—the second-most linked destination among IRA tweets. Although overall news content shared by trolls leaned moderate to conservative, we find troll accounts on both sides of the ideological spectrum, and these accounts maintain their political alignment. Links to YouTube videos were decidedly conservative, however. While mixed, this evidence is consistent with the IRA’s supporting the Republican campaign, but the IRA’s strategy was multifaceted, with an ideological division of labor among accounts. We contextualize these results as consistent with a pre-propaganda strategy. This work demonstrates the need to view political communication in the context of the broader media ecology, as governments exploit the interconnected information ecosystem to pursue covert propaganda strategies.}, keywords = {Elections, Propaganda, Russia, Twitter, USA, YouTube}, pubstate = {published}, tppubtype = {article} } This paper investigates online propaganda strategies of the Internet Research Agency (IRA)—Russian “trolls”—during the 2016 U.S. presidential election. We assess claims that the IRA sought either to (1) support Donald Trump or (2) sow discord among the U.S. public by analyzing hyperlinks contained in 108,781 IRA tweets. Our results show that although IRA accounts promoted links to both sides of the ideological spectrum, “conservative” trolls were more active than “liberal” ones. The IRA also shared content across social media platforms, particularly YouTube—the second-most linked destination among IRA tweets. Although overall news content shared by trolls leaned moderate to conservative, we find troll accounts on both sides of the ideological spectrum, and these accounts maintain their political alignment. Links to YouTube videos were decidedly conservative, however. While mixed, this evidence is consistent with the IRA’s supporting the Republican campaign, but the IRA’s strategy was multifaceted, with an ideological division of labor among accounts. We contextualize these results as consistent with a pre-propaganda strategy. This work demonstrates the need to view political communication in the context of the broader media ecology, as governments exploit the interconnected information ecosystem to pursue covert propaganda strategies. |
2019 |
Jan Zilinsky, Cristian Vaccari, Jonathan Nagler, Joshua A Tucker Don’t Republicans Tweet Too? Using Twitter to Assess the Consequences of Political Endorsements by Celebrities Journal Article Perspectives on Politics, 2019. Abstract | Links | Tags: Elections, Twitter @article{Zilinksy2019, title = {Don’t Republicans Tweet Too? Using Twitter to Assess the Consequences of Political Endorsements by Celebrities}, author = {Jan Zilinsky and Cristian Vaccari and Jonathan Nagler and Joshua A Tucker}, url = {https://www.cambridge.org/core/journals/perspectives-on-politics/article/dont-republicans-tweet-too-using-twitter-to-assess-the-consequences-of-political-endorsements-by-celebrities/B2915BB8FBD93D0555D8C3D77CB00E65}, year = {2019}, date = {2019-09-06}, journal = {Perspectives on Politics}, abstract = {Michael Jordan supposedly justified his decision to stay out of politics by noting that Republicans buy sneakers too. In the social media era, the name of the game for celebrities is engagement with fans. So why then do celebrities risk talking about politics on social media, which is likely to antagonize a portion of their fan base? With this question in mind, we analyze approximately 220,000 tweets from 83 celebrities who chose to endorse a presidential candidate in the 2016 U.S. presidential election campaign to assess whether there is a cost—defined in terms of engagement on Twitter—for celebrities who discuss presidential candidates. We also examine whether celebrities behave similarly to other campaign surrogates in being more likely to take on the “attack dog” role by going negative more often than going positive. More specifically, we document how often celebrities of distinct political preferences tweet about Donald Trump, Bernie Sanders, and Hillary Clinton, and we show that followers of opinionated celebrities do not withhold engagement when entertainers become politically mobilized and do indeed often go negative. Interestingly, in some cases political content from celebrities actually turns out to be more popular than typical lifestyle tweets.}, keywords = {Elections, Twitter}, pubstate = {published}, tppubtype = {article} } Michael Jordan supposedly justified his decision to stay out of politics by noting that Republicans buy sneakers too. In the social media era, the name of the game for celebrities is engagement with fans. So why then do celebrities risk talking about politics on social media, which is likely to antagonize a portion of their fan base? With this question in mind, we analyze approximately 220,000 tweets from 83 celebrities who chose to endorse a presidential candidate in the 2016 U.S. presidential election campaign to assess whether there is a cost—defined in terms of engagement on Twitter—for celebrities who discuss presidential candidates. We also examine whether celebrities behave similarly to other campaign surrogates in being more likely to take on the “attack dog” role by going negative more often than going positive. More specifically, we document how often celebrities of distinct political preferences tweet about Donald Trump, Bernie Sanders, and Hillary Clinton, and we show that followers of opinionated celebrities do not withhold engagement when entertainers become politically mobilized and do indeed often go negative. Interestingly, in some cases political content from celebrities actually turns out to be more popular than typical lifestyle tweets. |
Pablo Barberá, Andreu Casas, Jonathan Nagler, Patrick Egan, Richard Bonneau, John Jost, Joshua A Tucker Who Leads? Who Follows? Measuring Issue Attention and Agenda Setting by Legislators and the Mass Public Using Social Media Data Journal Article American Political Science Review, 2019. Abstract | Links | Tags: Methodology, Public opinion, Twitter @article{Barbera2019, title = {Who Leads? Who Follows? Measuring Issue Attention and Agenda Setting by Legislators and the Mass Public Using Social Media Data}, author = {Pablo Barberá and Andreu Casas and Jonathan Nagler and Patrick Egan and Richard Bonneau and John Jost and Joshua A Tucker}, url = {https://www.cambridge.org/core/journals/american-political-science-review/article/who-leads-who-follows-measuring-issue-attention-and-agenda-setting-by-legislators-and-the-mass-public-using-social-media-data/D855849CE288A241529E9EC2E4FBD3A8}, year = {2019}, date = {2019-07-12}, journal = {American Political Science Review}, abstract = {Are legislators responsive to the priorities of the public? Research demonstrates a strong correspondence between the issues about which the public cares and the issues addressed by politicians, but conclusive evidence about who leads whom in setting the political agenda has yet to be uncovered. We answer this question with fine-grained temporal analyses of Twitter messages by legislators and the public during the 113th US Congress. After employing an unsupervised method that classifies tweets sent by legislators and citizens into topics, we use vector autoregression models to explore whose priorities more strongly predict the relationship between citizens and politicians. We find that legislators are more likely to follow, than to lead, discussion of public issues, results that hold even after controlling for the agenda-setting effects of the media. We also find, however, that legislators are more likely to be responsive to their supporters than to the general public. }, keywords = {Methodology, Public opinion, Twitter}, pubstate = {published}, tppubtype = {article} } Are legislators responsive to the priorities of the public? Research demonstrates a strong correspondence between the issues about which the public cares and the issues addressed by politicians, but conclusive evidence about who leads whom in setting the political agenda has yet to be uncovered. We answer this question with fine-grained temporal analyses of Twitter messages by legislators and the public during the 113th US Congress. After employing an unsupervised method that classifies tweets sent by legislators and citizens into topics, we use vector autoregression models to explore whose priorities more strongly predict the relationship between citizens and politicians. We find that legislators are more likely to follow, than to lead, discussion of public issues, results that hold even after controlling for the agenda-setting effects of the media. We also find, however, that legislators are more likely to be responsive to their supporters than to the general public. |
Jennifer Larson, Jonathan Nagler, Jonathan Ronen, Joshua A Tucker Social Networks and Protest Participation: Evidence from 130 Million Twitter Users Journal Article American Journal of Political Science, 63 (3), pp. 690-705, 2019. Abstract | Links | Tags: Methodology, Protests, Twitter @article{Larson2019, title = {Social Networks and Protest Participation: Evidence from 130 Million Twitter Users}, author = {Jennifer Larson and Jonathan Nagler and Jonathan Ronen and Joshua A Tucker}, url = {https://doi.org/10.1111/ajps.12436}, year = {2019}, date = {2019-07-01}, journal = {American Journal of Political Science}, volume = {63}, number = {3}, pages = {690-705}, abstract = {Pinning down the role of social ties in the decision to protest has been notoriously elusive, largely due to data limitations. Social media and their global use by protesters offer an unprecedented opportunity to observe real‐time social ties and online behavior, though often without an attendant measure of real‐world behavior. We collect data on Twitter activity during the 2015 Charlie Hebdo protest in Paris, which, unusually, record real‐world protest attendance and network structure measured beyond egocentric networks. We devise a test of social theories of protest that hold that participation depends on exposure to others' intentions and network position determines exposure. Our findings are strongly consistent with these theories, showing that protesters are significantly more connected to one another via direct, indirect, triadic, and reciprocated ties than comparable nonprotesters. These results offer the first large‐scale empirical support for the claim that social network structure has consequences for protest participation.}, keywords = {Methodology, Protests, Twitter}, pubstate = {published}, tppubtype = {article} } Pinning down the role of social ties in the decision to protest has been notoriously elusive, largely due to data limitations. Social media and their global use by protesters offer an unprecedented opportunity to observe real‐time social ties and online behavior, though often without an attendant measure of real‐world behavior. We collect data on Twitter activity during the 2015 Charlie Hebdo protest in Paris, which, unusually, record real‐world protest attendance and network structure measured beyond egocentric networks. We devise a test of social theories of protest that hold that participation depends on exposure to others' intentions and network position determines exposure. Our findings are strongly consistent with these theories, showing that protesters are significantly more connected to one another via direct, indirect, triadic, and reciprocated ties than comparable nonprotesters. These results offer the first large‐scale empirical support for the claim that social network structure has consequences for protest participation. |
Denis Stukal, Sergey Sanovich, Joshua A Tucker, Richard Bonneau For Whom the Bot Tolls: A Neural Networks Approach to Measuring Political Orientation of Twitter Bots in Russia Journal Article SAGE Open, 9 (2), 2019. Abstract | Links | Tags: Bots, Russia, Twitter @article{Stukal2019b, title = {For Whom the Bot Tolls: A Neural Networks Approach to Measuring Political Orientation of Twitter Bots in Russia }, author = {Denis Stukal and Sergey Sanovich and Joshua A Tucker and Richard Bonneau}, url = {https://doi.org/10.1177%2F2158244019827715}, doi = {10.1177/2158244019827715}, year = {2019}, date = {2019-04-12}, journal = {SAGE Open}, volume = {9}, number = {2}, abstract = {Computational propaganda and the use of automated accounts in social media have recently become the focus of public attention, with alleged Russian government activities abroad provoking particularly widespread interest. However, even in the Russian domestic context, where anecdotal evidence of state activity online goes back almost a decade, no public systematic attempt has been made to dissect the population of Russian social media bots by their political orientation. We address this gap by developing a deep neural network classifier that separates pro-regime, anti-regime, and neutral Russian Twitter bots. Our method relies on supervised machine learning and a new large set of labeled accounts, rather than externally obtained account affiliations or orientation of elites. We also illustrate the use of our method by applying it to bots operating in Russian political Twitter from 2015 to 2017 and show that both pro- and anti-Kremlin bots had a substantial presence on Twitter.}, keywords = {Bots, Russia, Twitter}, pubstate = {published}, tppubtype = {article} } Computational propaganda and the use of automated accounts in social media have recently become the focus of public attention, with alleged Russian government activities abroad provoking particularly widespread interest. However, even in the Russian domestic context, where anecdotal evidence of state activity online goes back almost a decade, no public systematic attempt has been made to dissect the population of Russian social media bots by their political orientation. We address this gap by developing a deep neural network classifier that separates pro-regime, anti-regime, and neutral Russian Twitter bots. Our method relies on supervised machine learning and a new large set of labeled accounts, rather than externally obtained account affiliations or orientation of elites. We also illustrate the use of our method by applying it to bots operating in Russian political Twitter from 2015 to 2017 and show that both pro- and anti-Kremlin bots had a substantial presence on Twitter. |
Alexandra Siegel, Evgenii Nikitin, Pablo Barberá, Joanna Sterling, Bethany Pullen, Richard Bonneau, Jonathan Nagler, Joshua A Tucker Trumping Hate on Twitter? Online Hate in the 2016 US Election and its Aftermath Online 2019. Abstract | Links | Tags: Elections, Twitter, USA @online{Siegel2019, title = {Trumping Hate on Twitter? Online Hate in the 2016 US Election and its Aftermath}, author = {Alexandra Siegel and Evgenii Nikitin and Pablo Barberá and Joanna Sterling and Bethany Pullen and Richard Bonneau and Jonathan Nagler and Joshua A Tucker}, url = {https://smappnyu.org/wp-content/uploads/2019/04/US_Election_Hate_Speech_2019_03_website.pdf https://smappnyu.org/wp-content/uploads/2019/04/US_Election_Hate_Speech_2019_03_website_appendix.pdf}, year = {2019}, date = {2019-04-06}, abstract = {To what extent did online hate speech and white nationalist rhetoric on Twitter increase over the course of Donald Trump’s 2016 presidential election campaign and its aftermath? The prevailing narrative suggests that Trump’s political rise—and his unexpected victory—lent legitimacy to and popularized bigoted rhetoric that was once relegated to the dark corners of the Internet. However, our analysis of over 750 million tweets related to the election, in addition to almost 400 million tweets from a random sample of American Twitter users, provides systematic evidence that hate speech did not increase on Twitter over this period. Using both machine-learning-augmented dictionary-based methods and a novel classification approach leveraging data from Reddit communities associated with the alt-right movement, we observe no persistent increase in hate speech or white nationalist language either over the course of the campaign or in the aftermath of Trump’s election. While key campaign events and policy announcements produced brief spikes in hateful language, these bursts quickly dissipated. Overall we find no empirical support for the proposition that Trump’s divisive campaign or election increased hate speech on Twitter.}, keywords = {Elections, Twitter, USA}, pubstate = {published}, tppubtype = {online} } To what extent did online hate speech and white nationalist rhetoric on Twitter increase over the course of Donald Trump’s 2016 presidential election campaign and its aftermath? The prevailing narrative suggests that Trump’s political rise—and his unexpected victory—lent legitimacy to and popularized bigoted rhetoric that was once relegated to the dark corners of the Internet. However, our analysis of over 750 million tweets related to the election, in addition to almost 400 million tweets from a random sample of American Twitter users, provides systematic evidence that hate speech did not increase on Twitter over this period. Using both machine-learning-augmented dictionary-based methods and a novel classification approach leveraging data from Reddit communities associated with the alt-right movement, we observe no persistent increase in hate speech or white nationalist language either over the course of the campaign or in the aftermath of Trump’s election. While key campaign events and policy announcements produced brief spikes in hateful language, these bursts quickly dissipated. Overall we find no empirical support for the proposition that Trump’s divisive campaign or election increased hate speech on Twitter. |
Gregory Eady, Jonathan Nagler, Andrew Guess, Jan Zilinsky, Joshua A Tucker How Many People Live in Political Bubbles on Social Media? Evidence From Linked Survey and Twitter Data. Journal Article SAGE Open, 2019. Abstract | Links | Tags: Echo Chambers, Information Flows, Twitter @article{Eady2019, title = {How Many People Live in Political Bubbles on Social Media? Evidence From Linked Survey and Twitter Data.}, author = {Gregory Eady and Jonathan Nagler and Andrew Guess and Jan Zilinsky and Joshua A Tucker}, url = {https://smappnyu.org/wp-content/uploads/2019/03/Bubbles.pdf}, doi = {10.1177/2158244019832705}, year = {2019}, date = {2019-02-28}, journal = {SAGE Open}, abstract = {A major point of debate in the study of the Internet and politics is the extent to which social media platforms encourage citizens to inhabit online “bubbles” or “echo chambers,” exposed primarily to ideologically congenial political information. To investigate this question, we link a representative survey of Americans with data from respondents’ public Twitter accounts (N = 1,496). We then quantify the ideological distributions of users’ online political and media environments by merging validated estimates of user ideology with the full set of accounts followed by our survey respondents (N = 642,345) and the available tweets posted by those accounts (N ~ 1.2 billion). We study the extent to which liberals and conservatives encounter counter-attitudinal messages in two distinct ways: (a) by the accounts they follow and (b) by the tweets they receive from those accounts, either directly or indirectly (via retweets). More than a third of respondents do not follow any media sources, but among those who do, we find a substantial amount of overlap (51%) in the ideological distributions of accounts followed by users on opposite ends of the political spectrum. At the same time, however, we find asymmetries in individuals’ willingness to venture into cross-cutting spaces, with conservatives more likely to follow media and political accounts classified as left-leaning than the reverse. Finally, we argue that such choices are likely tempered by online news watching behavior.}, keywords = {Echo Chambers, Information Flows, Twitter}, pubstate = {published}, tppubtype = {article} } A major point of debate in the study of the Internet and politics is the extent to which social media platforms encourage citizens to inhabit online “bubbles” or “echo chambers,” exposed primarily to ideologically congenial political information. To investigate this question, we link a representative survey of Americans with data from respondents’ public Twitter accounts (N = 1,496). We then quantify the ideological distributions of users’ online political and media environments by merging validated estimates of user ideology with the full set of accounts followed by our survey respondents (N = 642,345) and the available tweets posted by those accounts (N ~ 1.2 billion). We study the extent to which liberals and conservatives encounter counter-attitudinal messages in two distinct ways: (a) by the accounts they follow and (b) by the tweets they receive from those accounts, either directly or indirectly (via retweets). More than a third of respondents do not follow any media sources, but among those who do, we find a substantial amount of overlap (51%) in the ideological distributions of accounts followed by users on opposite ends of the political spectrum. At the same time, however, we find asymmetries in individuals’ willingness to venture into cross-cutting spaces, with conservatives more likely to follow media and political accounts classified as left-leaning than the reverse. Finally, we argue that such choices are likely tempered by online news watching behavior. |
Melanie Langer, John Jost, Richard Bonneau, Megan Metzger, Sharareh Noorbaloochi, Duncan Penfold-Brown Digital Dissent: An Analysis of the Motivational Contents of Tweets From an Occupy Wall Street Demonstration Journal Article Motivation Science, 5 (1), pp. 14-34, 2019. Abstract | Links | Tags: Protests, Twitter, USA @article{Langer2019, title = {Digital Dissent: An Analysis of the Motivational Contents of Tweets From an Occupy Wall Street Demonstration}, author = {Melanie Langer and John Jost and Richard Bonneau and Megan Metzger and Sharareh Noorbaloochi and Duncan Penfold-Brown}, url = {https://smappnyu.org/wp-content/uploads/2019/02/Digital-dissent_An-analysis-of-OWS-tweets.pdf}, year = {2019}, date = {2019-02-27}, journal = {Motivation Science}, volume = {5}, number = {1}, pages = {14-34}, abstract = {Social scientific models of protest activity emphasize instrumental motives associated with rational self-interest and beliefs about group efficacy and symbolic motives associated with social identification and anger at perceived injustice. Ideological processes are typically neglected, despite the fact that protest movements occur in a sociopolitical context in which some people are motivated to maintain the status quo, whereas others are motivated to challenge it. To investigate the role of ideology and other social psychological processes in protest participation, we used manual and machine-learning methods to analyze the contents of 23,810 tweets sent on the day of the May Day 2012 Occupy Wall Street demonstration along with an additional 664,937 tweets (sent by 8,244 unique users) during the 2-week lead-up to the demonstration. Results revealed that social identification and liberal ideology were significant independent predictors of protest participation. The effect of social identification was mediated by the expression of collective efficacy, justice concerns, ideological themes, and positive emotion. The effect of liberalism was mediated by the expression of ideological themes, but conservatives were more likely to express ideological backlash against Occupy Wall Street than liberals were to express ideological support for the movement or demonstration. The expression of self-interest and anger was either negatively related or unrelated to protest participation. This work illustrates the promise (and challenge) of using automated methods to analyze new, ecologically valid data sources for studying protest activity and its motivational underpinnings—thereby informing strategic campaigns that employ collective action tactics.}, keywords = {Protests, Twitter, USA}, pubstate = {published}, tppubtype = {article} } Social scientific models of protest activity emphasize instrumental motives associated with rational self-interest and beliefs about group efficacy and symbolic motives associated with social identification and anger at perceived injustice. Ideological processes are typically neglected, despite the fact that protest movements occur in a sociopolitical context in which some people are motivated to maintain the status quo, whereas others are motivated to challenge it. To investigate the role of ideology and other social psychological processes in protest participation, we used manual and machine-learning methods to analyze the contents of 23,810 tweets sent on the day of the May Day 2012 Occupy Wall Street demonstration along with an additional 664,937 tweets (sent by 8,244 unique users) during the 2-week lead-up to the demonstration. Results revealed that social identification and liberal ideology were significant independent predictors of protest participation. The effect of social identification was mediated by the expression of collective efficacy, justice concerns, ideological themes, and positive emotion. The effect of liberalism was mediated by the expression of ideological themes, but conservatives were more likely to express ideological backlash against Occupy Wall Street than liberals were to express ideological support for the movement or demonstration. The expression of self-interest and anger was either negatively related or unrelated to protest participation. This work illustrates the promise (and challenge) of using automated methods to analyze new, ecologically valid data sources for studying protest activity and its motivational underpinnings—thereby informing strategic campaigns that employ collective action tactics. |
Andrew Guess, Jonathan Nagler, Joshua A Tucker Less than you think: Prevalence and predictors of fake news dissemination on Facebook Journal Article Science Advances, 5 (1), 2019. Abstract | Links | Tags: Elections, Facebook, Fake News @article{Guess2019, title = {Less than you think: Prevalence and predictors of fake news dissemination on Facebook}, author = {Andrew Guess and Jonathan Nagler and Joshua A Tucker}, url = {https://smappnyu.org/wp-content/uploads/2019/01/Fake_News.pdf}, doi = {10.1126/sciadv.aau4586}, year = {2019}, date = {2019-01-09}, journal = {Science Advances}, volume = {5}, number = {1}, abstract = {So-called “fake news” has renewed concerns about the prevalence and effects of misinformation in political campaigns. Given the potential for widespread dissemination of this material, we examine the individual-level characteristics associated with sharing false articles during the 2016 U.S. presidential campaign. To do so, we uniquely link an original survey with respondents’ sharing activity as recorded in Facebook profile data. First and foremost, we find that sharing this content was a relatively rare activity. Conservatives were more likely to share articles from fake news domains, which in 2016 were largely pro-Trump in orientation, than liberals or moderates. We also find a strong age effect, which persists after controlling for partisanship and ideology: On average, users over 65 shared nearly seven times as many articles from fake news domains as the youngest age group.}, keywords = {Elections, Facebook, Fake News}, pubstate = {published}, tppubtype = {article} } So-called “fake news” has renewed concerns about the prevalence and effects of misinformation in political campaigns. Given the potential for widespread dissemination of this material, we examine the individual-level characteristics associated with sharing false articles during the 2016 U.S. presidential campaign. To do so, we uniquely link an original survey with respondents’ sharing activity as recorded in Facebook profile data. First and foremost, we find that sharing this content was a relatively rare activity. Conservatives were more likely to share articles from fake news domains, which in 2016 were largely pro-Trump in orientation, than liberals or moderates. We also find a strong age effect, which persists after controlling for partisanship and ideology: On average, users over 65 shared nearly seven times as many articles from fake news domains as the youngest age group. |
Denis Stukal, Joshua A Tucker, Sergey Sanovich, Richard Bonneau The Use of Twitter Bots in Russian Political Communication Online PONARS Eurasia 2019. Abstract | Links | Tags: Bots, Russia, Twitter @online{Stukal2019, title = {The Use of Twitter Bots in Russian Political Communication}, author = {Denis Stukal and Joshua A Tucker and Sergey Sanovich and Richard Bonneau}, url = {http://www.ponarseurasia.org/sites/default/files/policy-memos-pdf/Pepm564_Stukal-Sanovich-Bonneau-Tucker_Jan2019_0.pdf}, year = {2019}, date = {2019-01-04}, journal = {PONARS Eurasia}, volume = {564}, organization = {PONARS Eurasia}, abstract = {We find that despite public discussion that has largely focused on the actions of proKremlin bots, the other three categories are also quite active. Interestingly, we find that pro-Kremlin bots are slightly younger than either pro-opposition or pro-Kyiv bots, and that they were more active than the other types of bots during the period of high Russian involvement in the Ukrainian crisis in 2014. We also characterize the activity of these bots, finding that all of the political bots are much more likely to retweet content produced by other accounts than the neutral bots. However, neutral bots are more likely to produce tweets that have identical content to those produced by other bots. Finally, we use network analysis to illustrate that the sources of retweets from Russian political bots are mass media and active Twitter users whose political leanings correspond to bots’ political orientation. This provides additional evidence in support of the claim that bots are mostly used as amplifiers for political messages.}, keywords = {Bots, Russia, Twitter}, pubstate = {published}, tppubtype = {online} } We find that despite public discussion that has largely focused on the actions of proKremlin bots, the other three categories are also quite active. Interestingly, we find that pro-Kremlin bots are slightly younger than either pro-opposition or pro-Kyiv bots, and that they were more active than the other types of bots during the period of high Russian involvement in the Ukrainian crisis in 2014. We also characterize the activity of these bots, finding that all of the political bots are much more likely to retweet content produced by other accounts than the neutral bots. However, neutral bots are more likely to produce tweets that have identical content to those produced by other bots. Finally, we use network analysis to illustrate that the sources of retweets from Russian political bots are mass media and active Twitter users whose political leanings correspond to bots’ political orientation. This provides additional evidence in support of the claim that bots are mostly used as amplifiers for political messages. |
2018 |
Marko Klašnja, Pablo Barberá, Nicholas Beauchamp, Jonathan Nagler, Joshua A Tucker Measuring Public Opinion with Social Media Data Book Chapter Atkeson, Lonna Rae; Alvarez, Michael R (Ed.): Oxford Handbook of Polling and Survey Methods, pp. 555-582, Oxford University Press, 2018. Abstract | Links | Tags: Methodology, Public opinion @inbook{Klašnja2018, title = {Measuring Public Opinion with Social Media Data}, author = {Marko Klašnja and Pablo Barberá and Nicholas Beauchamp and Jonathan Nagler and Joshua A Tucker}, editor = {Lonna Rae Atkeson and Michael R Alvarez}, url = {http://www.oxfordhandbooks.com/view/10.1093/oxfordhb/9780190213299.001.0001/oxfordhb-9780190213299-e-3}, doi = {10.1093/oxfordhb/9780190213299.013.3}, year = {2018}, date = {2018-11-20}, booktitle = {Oxford Handbook of Polling and Survey Methods}, pages = {555-582}, publisher = {Oxford University Press}, abstract = {This chapter examines the use of social networking sites such as Twitter in measuring public opinion. It first considers the opportunities and challenges that are involved in conducting public opinion surveys using social media data. Three challenges are discussed: identifying political opinion, representativeness of social media users, and aggregating from individual responses to public opinion. The chapter outlines some of the strategies for overcoming these challenges and proceeds by highlighting some of the novel uses for social media that have fewer direct analogs in traditional survey work. Finally, it suggests new directions for a research agenda in using social media for public opinion work.}, keywords = {Methodology, Public opinion}, pubstate = {published}, tppubtype = {inbook} } This chapter examines the use of social networking sites such as Twitter in measuring public opinion. It first considers the opportunities and challenges that are involved in conducting public opinion surveys using social media data. Three challenges are discussed: identifying political opinion, representativeness of social media users, and aggregating from individual responses to public opinion. The chapter outlines some of the strategies for overcoming these challenges and proceeds by highlighting some of the novel uses for social media that have fewer direct analogs in traditional survey work. Finally, it suggests new directions for a research agenda in using social media for public opinion work. |
Andrew Guess, Kevin Munger, Jonathan Nagler, Joshua A Tucker How Accurate Are Survey Responses on Social Media and Politics? Journal Article Political Communication, 2018. Abstract | Links | Tags: Facebook, Methodology, SMaPP Survey, Twitter @article{Guess2018, title = {How Accurate Are Survey Responses on Social Media and Politics?}, author = {Andrew Guess and Kevin Munger and Jonathan Nagler and Joshua A Tucker}, url = {https://www.tandfonline.com/doi/abs/10.1080/10584609.2018.1504840?journalCode=upcp20}, year = {2018}, date = {2018-11-05}, journal = {Political Communication}, abstract = {How accurate are survey-based measures of social media use, in particular about political topics? We answer this question by linking original survey data collected during the U.S. 2016 election campaign with respondents’ observed social media activity. We use supervised machine learning to classify whether these Twitter and Facebook account data are content related to politics. We then benchmark our survey measures on frequency of posting about politics and the number of political figures followed. We find that, on average, our self-reported survey measures tend to correlate with observed social media activity. At the same time, we also find a worrying amount of individual-level discrepancy and problems related to extreme outliers. Our recommendations are twofold. The first is for survey questions about social media use to provide respondents with options covering a wider range of activity, especially in the long tail. The second is for survey questions to include specific content and anchors defining what it means for a post to be “about politics.”}, keywords = {Facebook, Methodology, SMaPP Survey, Twitter}, pubstate = {published}, tppubtype = {article} } How accurate are survey-based measures of social media use, in particular about political topics? We answer this question by linking original survey data collected during the U.S. 2016 election campaign with respondents’ observed social media activity. We use supervised machine learning to classify whether these Twitter and Facebook account data are content related to politics. We then benchmark our survey measures on frequency of posting about politics and the number of political figures followed. We find that, on average, our self-reported survey measures tend to correlate with observed social media activity. At the same time, we also find a worrying amount of individual-level discrepancy and problems related to extreme outliers. Our recommendations are twofold. The first is for survey questions about social media use to provide respondents with options covering a wider range of activity, especially in the long tail. The second is for survey questions to include specific content and anchors defining what it means for a post to be “about politics.” |
Alexandra Siegel Twitter Wars: Sunni-Shia Conflict and Cooperation in the Digital Age Book Chapter Wehrey, Frederic (Ed.): Beyond Sunni and Shia: The Roots of Sectarianism in a Changing Middle East, pp. 157-180, Hurst Publishers, 2018. Abstract | Links | Tags: Propaganda, Twitter @inbook{Siegel2018b, title = {Twitter Wars: Sunni-Shia Conflict and Cooperation in the Digital Age}, author = {Alexandra Siegel}, editor = {Frederic Wehrey}, url = {https://www.jstor.org/stable/resrep13025?seq=1#metadata_info_tab_contents}, year = {2018}, date = {2018-08-15}, booktitle = {Beyond Sunni and Shia: The Roots of Sectarianism in a Changing Middle East}, pages = {157-180}, publisher = {Hurst Publishers}, abstract = {Amid mounting death tolls in Iraq, Syria, and Yemen, sectarian discourse is on the rise across the Arab world—particularly in the online sphere, where extremist voices are amplified and violent imagery and rhetoric spreads rapidly. Despite this, social media also provides a space for cross-sectarian discourse and activism. Analysis of over 7 million Arabic tweets from February to August 2015 suggests that violent events and social network structures play key roles in the transmission of this sectarian and countersectarian rhetoric on Twitter.}, keywords = {Propaganda, Twitter}, pubstate = {published}, tppubtype = {inbook} } Amid mounting death tolls in Iraq, Syria, and Yemen, sectarian discourse is on the rise across the Arab world—particularly in the online sphere, where extremist voices are amplified and violent imagery and rhetoric spreads rapidly. Despite this, social media also provides a space for cross-sectarian discourse and activism. Analysis of over 7 million Arabic tweets from February to August 2015 suggests that violent events and social network structures play key roles in the transmission of this sectarian and countersectarian rhetoric on Twitter. |
Kevin Munger, Richard Bonneau, Jonathan Nagler, Joshua A Tucker Elites Tweet to Get Feet Off the Streets: Measuring Regime Social Media Strategies During Protest Journal Article Political Science Research and Methods, pp. 1-20, 2018. Abstract | Links | Tags: Protests, Venezuela @article{Munger2018, title = {Elites Tweet to Get Feet Off the Streets: Measuring Regime Social Media Strategies During Protest}, author = {Kevin Munger and Richard Bonneau and Jonathan Nagler and Joshua A Tucker}, url = {https://doi.org/10.1017/psrm.2018.3}, year = {2018}, date = {2018-03-21}, journal = {Political Science Research and Methods}, pages = {1-20}, abstract = {As non-democratic regimes have adapted to the proliferation of social media, they have began actively engaging with Twitter to enhance regime resilience. Using data taken from the Twitter accounts of Venezuelan legislators during the 2014 anti-Maduro protests in Venezuela, we fit a topic model on the text of the tweets and analyze patterns in hashtag use by the two coalitions. We argue that the regime’s best strategy in the face of an existential threat like the narrative developed by La Salida and promoted on Twitter was to advance many competing narratives that addressed issues unrelated to the opposition’s criticism. Our results show that the two coalitions pursued different rhetorical strategies in keeping with our predictions about managing the conflict advanced by the protesters. This article extends the literature on social media use during protests by focusing on active engagement with social media on the part of the regime. This approach corroborates and expands on recent research on inferring regime strategies from propaganda and censorship.}, keywords = {Protests, Venezuela}, pubstate = {published}, tppubtype = {article} } As non-democratic regimes have adapted to the proliferation of social media, they have began actively engaging with Twitter to enhance regime resilience. Using data taken from the Twitter accounts of Venezuelan legislators during the 2014 anti-Maduro protests in Venezuela, we fit a topic model on the text of the tweets and analyze patterns in hashtag use by the two coalitions. We argue that the regime’s best strategy in the face of an existential threat like the narrative developed by La Salida and promoted on Twitter was to advance many competing narratives that addressed issues unrelated to the opposition’s criticism. Our results show that the two coalitions pursued different rhetorical strategies in keeping with our predictions about managing the conflict advanced by the protesters. This article extends the literature on social media use during protests by focusing on active engagement with social media on the part of the regime. This approach corroborates and expands on recent research on inferring regime strategies from propaganda and censorship. |
Joshua A Tucker, Andrew Guess, Pablo Barberá, Cristian Vaccari, Alexandra Siegel, Sergey Sanovich, Denis Stukal, Brendan Nyhan Hewlett Foundation 2018. Abstract | Links | Tags: Fake News, Propaganda @online{Tucker2018, title = {Social Media, Political Polarization, and Political Disinformation: A Review of the Scientific Literature}, author = {Joshua A Tucker and Andrew Guess and Pablo Barberá and Cristian Vaccari and Alexandra Siegel and Sergey Sanovich and Denis Stukal and Brendan Nyhan}, url = {https://ssrn.com/abstract=3144139}, doi = {http://dx.doi.org/10.2139/ssrn.3144139}, year = {2018}, date = {2018-03-19}, organization = {Hewlett Foundation}, abstract = {The following report is intended to provide an overview of the current state of the literature on the relationship between social media; political polarization; and political “disinformation,” a term used to encompass a wide range of types of information about politics found online, including “fake news,” rumors, deliberately factually incorrect information, inadvertently factually incorrect information, politically slanted information, and “hyperpartisan” news. The review of the literature is provided in six separate sections, each of which can be read individually but that cumulatively are intended to provide an overview of what is known—and unknown—about the relationship between social media, political polarization, and disinformation. The report concludes by identifying key gaps in our understanding of these phenomena and the data that are needed to address them.}, keywords = {Fake News, Propaganda}, pubstate = {published}, tppubtype = {online} } The following report is intended to provide an overview of the current state of the literature on the relationship between social media; political polarization; and political “disinformation,” a term used to encompass a wide range of types of information about politics found online, including “fake news,” rumors, deliberately factually incorrect information, inadvertently factually incorrect information, politically slanted information, and “hyperpartisan” news. The review of the literature is provided in six separate sections, each of which can be read individually but that cumulatively are intended to provide an overview of what is known—and unknown—about the relationship between social media, political polarization, and disinformation. The report concludes by identifying key gaps in our understanding of these phenomena and the data that are needed to address them. |
Joanna Sterling, John Jost Moral Discourse in the Twitterverse Journal Article Journal of Language and Politics, 17 (2), pp. 195-221, 2018. Abstract | Links | Tags: Twitter, USA @article{Sterling2018, title = {Moral Discourse in the Twitterverse}, author = {Joanna Sterling and John Jost}, url = {https://benjamins.com/content/home#catalog/journals/jlp.17034.ste/details}, year = {2018}, date = {2018-03-01}, journal = {Journal of Language and Politics}, volume = {17}, number = {2}, pages = {195-221}, abstract = {We analyzed Twitter language to explore hypotheses derived from moral foundations theory, which suggests that liberals and conservatives prioritize different values. In Study 1, we captured 11 million tweets from nearly 25,000 U.S. residents and observed that liberals expressed fairness concerns more often than conservatives, whereas conservatives were more likely to express concerns about group loyalty, authority, and purity. Increasing political sophistication exacerbated ideological differences in authority and group loyalty. At low levels of sophistication, liberals used more harm language, but at high levels of sophistication conservatives referenced harm more often. In Study 2, we analyzed 59,000 tweets from 388 members of the U.S. Congress. Liberal legislators used more fairness- and harm-related words, whereas conservative legislators used more authority-related words. Unexpectedly, liberal legislators used more language pertaining to group loyalty and purity. Follow-up analyses suggest that liberals and conservatives in Congress use similar words to emphasize different policy priorities.}, keywords = {Twitter, USA}, pubstate = {published}, tppubtype = {article} } We analyzed Twitter language to explore hypotheses derived from moral foundations theory, which suggests that liberals and conservatives prioritize different values. In Study 1, we captured 11 million tweets from nearly 25,000 U.S. residents and observed that liberals expressed fairness concerns more often than conservatives, whereas conservatives were more likely to express concerns about group loyalty, authority, and purity. Increasing political sophistication exacerbated ideological differences in authority and group loyalty. At low levels of sophistication, liberals used more harm language, but at high levels of sophistication conservatives referenced harm more often. In Study 2, we analyzed 59,000 tweets from 388 members of the U.S. Congress. Liberal legislators used more fairness- and harm-related words, whereas conservative legislators used more authority-related words. Unexpectedly, liberal legislators used more language pertaining to group loyalty and purity. Follow-up analyses suggest that liberals and conservatives in Congress use similar words to emphasize different policy priorities. |
John Jost, Pablo Barberá, Richard Bonneau, Melanie Langer, Megan Metzger, Jonathan Nagler, Joanna Sterling, Joshua A Tucker How Social Media Facilitates Political Protest: Information, Motivation, and Social Networks Journal Article Advances in Political Psychology, 39 (S1), pp. 85-118, 2018. Abstract | Links | Tags: Facebook, Information Flows, Protests, Twitter @article{Jost2018b, title = {How Social Media Facilitates Political Protest: Information, Motivation, and Social Networks}, author = {John Jost and Pablo Barberá and Richard Bonneau and Melanie Langer and Megan Metzger and Jonathan Nagler and Joanna Sterling and Joshua A Tucker}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/pops.12478}, year = {2018}, date = {2018-02-13}, journal = {Advances in Political Psychology}, volume = {39}, number = {S1}, pages = {85-118}, abstract = {It is often claimed that social media platforms such as Facebook and Twitter are profoundly shaping political participation, especially when it comes to protest behavior. Whether or not this is the case, the analysis of “Big Data” generated by social media usage offers unprecedented opportunities to observe complex, dynamic effects associated with large‐scale collective action and social movements. In this article, we summarize evidence from studies of protest movements in the United States, Spain, Turkey, and Ukraine demonstrating that: (1) Social media platforms facilitate the exchange of information that is vital to the coordination of protest activities, such as news about transportation, turnout, police presence, violence, medical services, and legal support; (2) in addition, social media platforms facilitate the exchange of emotional and motivational contents in support of and opposition to protest activity, including messages emphasizing anger, social identification, group efficacy, and concerns about fairness, justice, and deprivation as well as explicitly ideological themes; and (3) structural characteristics of online social networks, which may differ as a function of political ideology, have important implications for information exposure and the success or failure of organizational efforts. Next, we issue a brief call for future research on a topic that is understudied but fundamental to appreciating the role of social media in facilitating political participation, namely friendship. In closing, we liken the situation confronted by researchers who are harvesting vast quantities of social media data to that of systems biologists in the early days of genome sequencing.}, keywords = {Facebook, Information Flows, Protests, Twitter}, pubstate = {published}, tppubtype = {article} } It is often claimed that social media platforms such as Facebook and Twitter are profoundly shaping political participation, especially when it comes to protest behavior. Whether or not this is the case, the analysis of “Big Data” generated by social media usage offers unprecedented opportunities to observe complex, dynamic effects associated with large‐scale collective action and social movements. In this article, we summarize evidence from studies of protest movements in the United States, Spain, Turkey, and Ukraine demonstrating that: (1) Social media platforms facilitate the exchange of information that is vital to the coordination of protest activities, such as news about transportation, turnout, police presence, violence, medical services, and legal support; (2) in addition, social media platforms facilitate the exchange of emotional and motivational contents in support of and opposition to protest activity, including messages emphasizing anger, social identification, group efficacy, and concerns about fairness, justice, and deprivation as well as explicitly ideological themes; and (3) structural characteristics of online social networks, which may differ as a function of political ideology, have important implications for information exposure and the success or failure of organizational efforts. Next, we issue a brief call for future research on a topic that is understudied but fundamental to appreciating the role of social media in facilitating political participation, namely friendship. In closing, we liken the situation confronted by researchers who are harvesting vast quantities of social media data to that of systems biologists in the early days of genome sequencing. |
Melanie Langer, John Jost, Richard Bonneau, Duncan Penfold-Brown, Sharareh Noorbaloochi Digital Dissent: An Analysis of the Motivational Contents of Tweets From an Occupy Wall Street Demonstration Journal Article Motivation Science, Advance online publication , 2018. Abstract | Links | Tags: Protests, Public opinion, Twitter, USA @article{Langer2018, title = {Digital Dissent: An Analysis of the Motivational Contents of Tweets From an Occupy Wall Street Demonstration}, author = {Melanie Langer and John Jost and Richard Bonneau and Duncan Penfold-Brown and Sharareh Noorbaloochi}, url = {https://www.researchgate.net/publication/322880711_Digital_Dissent_An_Analysis_of_the_Motivational_Contents_of_Tweets_From_an_Occupy_Wall_Street_Demonstration}, year = {2018}, date = {2018-02-01}, journal = {Motivation Science}, volume = {Advance online publication}, abstract = {Social scientific models of protest activity emphasize instrumental motives associated with rational self-interest and beliefs about group efficacy and symbolic motives associated with social identification and anger at perceived injustice. Ideological processes are typically neglected, despite the fact that protest movements occur in a sociopolitical context in which some people are motivated to maintain the status quo, whereas others are motivated to challenge it. To investigate the role of ideology and other social psychological processes in protest participation, we used manual and machine-learning methods to analyze the contents of 23,810 tweets sent on the day of the May Day 2012 Occupy Wall Street demonstration along with an additional 664,937 tweets (sent by 8,244 unique users) during the 2-week lead-up to the demonstration. Results revealed that social identification and liberal ideology were significant independent predictors of protest participation. The effect of social identification was mediated by the expression of collective efficacy, justice concerns, ideological themes, and positive emotion. The effect of liberalism was mediated by the expression of ideological themes, but conservatives were more likely to express ideological backlash against Occupy Wall Street than liberals were to express ideological support for the movement or demonstration. The expression of self-interest and anger was either negatively related or unrelated to protest participation. This work illustrates the promise (and challenge) of using automated methods to analyze new, ecologically valid data sources for studying protest activity and its motivational underpinnings—thereby informing strategic campaigns that employ collective action tactics.}, keywords = {Protests, Public opinion, Twitter, USA}, pubstate = {published}, tppubtype = {article} } Social scientific models of protest activity emphasize instrumental motives associated with rational self-interest and beliefs about group efficacy and symbolic motives associated with social identification and anger at perceived injustice. Ideological processes are typically neglected, despite the fact that protest movements occur in a sociopolitical context in which some people are motivated to maintain the status quo, whereas others are motivated to challenge it. To investigate the role of ideology and other social psychological processes in protest participation, we used manual and machine-learning methods to analyze the contents of 23,810 tweets sent on the day of the May Day 2012 Occupy Wall Street demonstration along with an additional 664,937 tweets (sent by 8,244 unique users) during the 2-week lead-up to the demonstration. Results revealed that social identification and liberal ideology were significant independent predictors of protest participation. The effect of social identification was mediated by the expression of collective efficacy, justice concerns, ideological themes, and positive emotion. The effect of liberalism was mediated by the expression of ideological themes, but conservatives were more likely to express ideological backlash against Occupy Wall Street than liberals were to express ideological support for the movement or demonstration. The expression of self-interest and anger was either negatively related or unrelated to protest participation. This work illustrates the promise (and challenge) of using automated methods to analyze new, ecologically valid data sources for studying protest activity and its motivational underpinnings—thereby informing strategic campaigns that employ collective action tactics. |
Alexandra Siegel, Joshua A Tucker The Islamic State’s Information Warfare: Measuring the Success of ISIS’ Online Strategy Journal Article Journal of Language and Politics, 17 (2), pp. 258-280, 2018. Abstract | Links | Tags: Information Flows, Propaganda, Twitter @article{Siegel2018b, title = {The Islamic State’s Information Warfare: Measuring the Success of ISIS’ Online Strategy}, author = {Alexandra Siegel and Joshua A Tucker}, url = {https://www.jbe-platform.com/content/journals/10.1075/jlp.17005.sie}, year = {2018}, date = {2018-01-08}, journal = {Journal of Language and Politics}, volume = {17}, number = {2}, pages = {258-280}, abstract = {How successful is the Islamic State’s online strategy? To what extent does the organization achieve its goals of attracting a global audience, broadcasting its military successes, and marketing the Caliphate? Using Twitter and YouTube search data, collected throughout 2015 and early 2016, we assess how suspected ISIS accounts, sympathizers, and opponents behave across two social media platforms, offering key insights into the successes and limitations of ISIS’s information warfare strategy. Analyzing the tweet content and metadata from 16,364 suspected ISIS accounts, we find that a core network of ISIS Twitter users are producing linguistically diverse narratives, touting battlefield victories and depicting utopian life in the Caliphate. Furthermore, a dataset of over 70 million tweets, as well as analysis YouTube search data, indicates that although pro-ISIS content spreads globally and remains on message, it is far less prolific than anti-ISIS content. However, this anti-ISIS content is not necessarily anti-extremist or aligned with Western policy goals.}, keywords = {Information Flows, Propaganda, Twitter}, pubstate = {published}, tppubtype = {article} } How successful is the Islamic State’s online strategy? To what extent does the organization achieve its goals of attracting a global audience, broadcasting its military successes, and marketing the Caliphate? Using Twitter and YouTube search data, collected throughout 2015 and early 2016, we assess how suspected ISIS accounts, sympathizers, and opponents behave across two social media platforms, offering key insights into the successes and limitations of ISIS’s information warfare strategy. Analyzing the tweet content and metadata from 16,364 suspected ISIS accounts, we find that a core network of ISIS Twitter users are producing linguistically diverse narratives, touting battlefield victories and depicting utopian life in the Caliphate. Furthermore, a dataset of over 70 million tweets, as well as analysis YouTube search data, indicates that although pro-ISIS content spreads globally and remains on message, it is far less prolific than anti-ISIS content. However, this anti-ISIS content is not necessarily anti-extremist or aligned with Western policy goals. |
Sergey Sanovich, Denis Stukal, Joshua A Tucker Turning the Virtual Tables: Government Strategies for Addressing Online Opposition with an Application to Russia Journal Article Comparative Politics, 50 (3), pp. 435-454, 2018. Links | Tags: Bots, Propaganda, Russia @article{Sanovich2018, title = {Turning the Virtual Tables: Government Strategies for Addressing Online Opposition with an Application to Russia}, author = {Sergey Sanovich and Denis Stukal and Joshua A Tucker}, url = {https://s18798.pcdn.co/smapp/wp-content/uploads/sites/1693/2018/04/Sanovich_et_al_2018.pdf}, year = {2018}, date = {2018-01-01}, journal = {Comparative Politics}, volume = {50}, number = {3}, pages = {435-454}, keywords = {Bots, Propaganda, Russia}, pubstate = {published}, tppubtype = {article} } |
2017 |
William Brady, Julian Wills, John Jost, Joshua A Tucker, Jay Van Bavel Emotion shapes the diffusion of moralized content in social networks Journal Article Proceedings of the National Academy of Sciences, 2017. Abstract | Links | Tags: Information Flows, Twitter @article{Brady2017, title = {Emotion shapes the diffusion of moralized content in social networks}, author = {William Brady and Julian Wills and John Jost and Joshua A Tucker and Jay Van Bavel}, url = {http://www.psych.nyu.edu/vanbavel/lab/documents/Brady.etal.2017.PNAS.pdf}, year = {2017}, date = {2017-05-23}, journal = {Proceedings of the National Academy of Sciences}, abstract = {Political debate concerning moralized issues is increasingly common in online social networks. However, moral psychology has yet to incorporate the study of social networks to investigate processes by which some moral ideas spread more rapidly or broadly than others. Here, we show that the expression of moral emotion is key for the spread of moral and political ideas in online social networks, a process we call “moral contagion.” Using a large sample of social media communications about three polarizing moral/political issues (n = 563,312), we observed that the presence of moral-emotional words in messages increased their diffusion by a factor of 20% for each additional word. Furthermore, we found that moral contagion was bounded by group membership; moral-emotional language increased diffusion more strongly within liberal and conservative networks, and less between them. Our results highlight the importance of emotion in the social transmission of moral ideas and also demonstrate the utility of social network methods for studying morality. These findings offer insights into how people are exposed to moral and political ideas through social networks, thus expanding models of social influence and group polarization as people become increasingly immersed in social media networks.}, keywords = {Information Flows, Twitter}, pubstate = {published}, tppubtype = {article} } Political debate concerning moralized issues is increasingly common in online social networks. However, moral psychology has yet to incorporate the study of social networks to investigate processes by which some moral ideas spread more rapidly or broadly than others. Here, we show that the expression of moral emotion is key for the spread of moral and political ideas in online social networks, a process we call “moral contagion.” Using a large sample of social media communications about three polarizing moral/political issues (n = 563,312), we observed that the presence of moral-emotional words in messages increased their diffusion by a factor of 20% for each additional word. Furthermore, we found that moral contagion was bounded by group membership; moral-emotional language increased diffusion more strongly within liberal and conservative networks, and less between them. Our results highlight the importance of emotion in the social transmission of moral ideas and also demonstrate the utility of social network methods for studying morality. These findings offer insights into how people are exposed to moral and political ideas through social networks, thus expanding models of social influence and group polarization as people become increasingly immersed in social media networks. |
Kevin Munger Tweetment Effects on the Tweeted: Experimentally Reducing Racist Harassment Journal Article Political Behavior, 39 (3), pp. 629-649, 2017. Abstract | Links | Tags: Experiments, Twitter @article{Munger2017, title = {Tweetment Effects on the Tweeted: Experimentally Reducing Racist Harassment}, author = {Kevin Munger}, url = {https://link.springer.com/article/10.1007/s11109-016-9373-5}, year = {2017}, date = {2017-02-01}, journal = {Political Behavior}, volume = {39}, number = {3}, pages = {629-649}, abstract = {I conduct an experiment which examines the impact of group norm promotion and social sanctioning on racist online harassment. Racist online harassment de-mobilizes the minorities it targets, and the open, unopposed expression of racism in a public forum can legitimize racist viewpoints and prime ethnocentrism. I employ an intervention designed to reduce the use of anti-black racist slurs by white men on Twitter. I collect a sample of Twitter users who have harassed other users and use accounts I control (“bots”) to sanction the harassers. By varying the identity of the bots between in-group (white man) and out-group (black man) and by varying the number of Twitter followers each bot has, I find that subjects who were sanctioned by a high-follower white male significantly reduced their use of a racist slur. This paper extends findings from lab experiments to a naturalistic setting using an objective, behavioral outcome measure and a continuous 2-month data collection period. This represents an advance in the study of prejudiced behavior.}, keywords = {Experiments, Twitter}, pubstate = {published}, tppubtype = {article} } I conduct an experiment which examines the impact of group norm promotion and social sanctioning on racist online harassment. Racist online harassment de-mobilizes the minorities it targets, and the open, unopposed expression of racism in a public forum can legitimize racist viewpoints and prime ethnocentrism. I employ an intervention designed to reduce the use of anti-black racist slurs by white men on Twitter. I collect a sample of Twitter users who have harassed other users and use accounts I control (“bots”) to sanction the harassers. By varying the identity of the bots between in-group (white man) and out-group (black man) and by varying the number of Twitter followers each bot has, I find that subjects who were sanctioned by a high-follower white male significantly reduced their use of a racist slur. This paper extends findings from lab experiments to a naturalistic setting using an objective, behavioral outcome measure and a continuous 2-month data collection period. This represents an advance in the study of prejudiced behavior. |
Joshua A Tucker, Yannis Theocharis, Margaret Roberts, Pablo Barberá From Liberation to Turmoil: Social Media and Democracy Journal Article The Journal of Democracy, 28 (4), pp. 46-59, 2017. Abstract | Links | Tags: Protests @article{Tucker2017, title = {From Liberation to Turmoil: Social Media and Democracy}, author = {Joshua A Tucker and Yannis Theocharis and Margaret Roberts and Pablo Barberá}, url = {https://www.journalofdemocracy.org/article/liberation-turmoil-social-media-and-democracy}, year = {2017}, date = {2017-01-07}, journal = {The Journal of Democracy}, volume = {28}, number = {4}, pages = {46-59}, abstract = {How can one technology—social media—simultaneously give rise to hopes for liberation in authoritarian regimes, be used for repression by these same regimes, and be harnessed by antisystem actors in democracy? We present a simple framework for reconciling these contradictory developments based on two propositions: 1) that social media give voice to those previously excluded from political discussion by traditional media, and 2) that although social media democratize access to information, the platforms themselves are neither inherently democratic nor nondemocratic, but represent a tool political actors can use for a variety of goals, including, paradoxically, illiberal goals.}, keywords = {Protests}, pubstate = {published}, tppubtype = {article} } How can one technology—social media—simultaneously give rise to hopes for liberation in authoritarian regimes, be used for repression by these same regimes, and be harnessed by antisystem actors in democracy? We present a simple framework for reconciling these contradictory developments based on two propositions: 1) that social media give voice to those previously excluded from political discussion by traditional media, and 2) that although social media democratize access to information, the platforms themselves are neither inherently democratic nor nondemocratic, but represent a tool political actors can use for a variety of goals, including, paradoxically, illiberal goals. |
Denis Stukal, Sergey Sanovich, Richard Bonneau, Joshua A Tucker Detecting Bots on Russian Political Twitter Journal Article Big Data, 5 (4), pp. 310-324, 2017. Abstract | Links | Tags: Bots, Russia, Twitter @article{Stukal2017, title = {Detecting Bots on Russian Political Twitter}, author = {Denis Stukal and Sergey Sanovich and Richard Bonneau and Joshua A Tucker}, url = {http://online.liebertpub.com/doi/full/10.1089/big.2017.0038}, year = {2017}, date = {2017-01-05}, journal = {Big Data}, volume = {5}, number = {4}, pages = {310-324}, abstract = {Automated and semiautomated Twitter accounts, bots, have recently gained significant public attention due to their potential interference in the political realm. In this study, we develop a methodology for detecting bots on Twitter using an ensemble of classifiers and apply it to study bot activity within political discussions in the Russian Twittersphere. We focus on the interval from February 2014 to December 2015, an especially consequential period in Russian politics. Among accounts actively Tweeting about Russian politics, we find that on the majority of days, the proportion of Tweets produced by bots exceeds 50%. We reveal bot characteristics that distinguish them from humans in this corpus, and find that the software platform used for Tweeting is among the best predictors of bots. Finally, we find suggestive evidence that one prominent activity that bots were involved in on Russian political Twitter is the spread of news stories and promotion of media who produce them.}, keywords = {Bots, Russia, Twitter}, pubstate = {published}, tppubtype = {article} } Automated and semiautomated Twitter accounts, bots, have recently gained significant public attention due to their potential interference in the political realm. In this study, we develop a methodology for detecting bots on Twitter using an ensemble of classifiers and apply it to study bot activity within political discussions in the Russian Twittersphere. We focus on the interval from February 2014 to December 2015, an especially consequential period in Russian politics. Among accounts actively Tweeting about Russian politics, we find that on the majority of days, the proportion of Tweets produced by bots exceeds 50%. We reveal bot characteristics that distinguish them from humans in this corpus, and find that the software platform used for Tweeting is among the best predictors of bots. Finally, we find suggestive evidence that one prominent activity that bots were involved in on Russian political Twitter is the spread of news stories and promotion of media who produce them. |
Megan Metzger, Joshua A Tucker Social Media and EuroMaidan: A Review Essay Journal Article Slavic Review, 76 (1), pp. 169-191, 2017. Abstract | Links | Tags: Protests, Twitter, Ukraine @article{Metzger2017, title = {Social Media and EuroMaidan: A Review Essay}, author = {Megan Metzger and Joshua A Tucker}, url = {https://www.cambridge.org/core/journals/slavic-review/article/social-media-and-euromaidan-a-review-essay/D4AF4BDCBE35D03421456EA26CA7F528}, year = {2017}, date = {2017-01-04}, journal = {Slavic Review}, volume = {76}, number = {1}, pages = {169-191}, abstract = {As more than a billion people had done previously, on November 21, 2013, Ukrainian journalist and activist Mustafa Nayem wrote a Facebook post; this post, however, would have a much larger impact on subsequent political developments than most that had preceded it. Frustrated with President Viktor Yanukovych’s decision not to sign a long-promised association agreement with the European Union, Nayem asked others who shared his frustration to comment on his post. Even more importantly, Nayem wrote that if the post received at least 1000 comments from people willing to join him, they should all go to Independence Square to protest. And indeed they did: starting with just a few thousand people, the protests would swell to be the largest since Ukraine’s independence, particularly after police used force against protesters at the end of November 2013. Eventually, these protests led to the resignation of the government, the exile of the former president, and indirectly to the secession of Crimea and the ongoing conflict in the eastern part of the country.}, keywords = {Protests, Twitter, Ukraine}, pubstate = {published}, tppubtype = {article} } As more than a billion people had done previously, on November 21, 2013, Ukrainian journalist and activist Mustafa Nayem wrote a Facebook post; this post, however, would have a much larger impact on subsequent political developments than most that had preceded it. Frustrated with President Viktor Yanukovych’s decision not to sign a long-promised association agreement with the European Union, Nayem asked others who shared his frustration to comment on his post. Even more importantly, Nayem wrote that if the post received at least 1000 comments from people willing to join him, they should all go to Independence Square to protest. And indeed they did: starting with just a few thousand people, the protests would swell to be the largest since Ukraine’s independence, particularly after police used force against protesters at the end of November 2013. Eventually, these protests led to the resignation of the government, the exile of the former president, and indirectly to the secession of Crimea and the ongoing conflict in the eastern part of the country. |
Kevin Jones, Sharareh Noorbaloochi, John Jost, Richard Bonneau, Jonathan Nagler, Joshua A Tucker Liberal and Conservative Values: What We Can Learn from Congressional Tweets Journal Article Political Psychology, 39 (2), pp. 423-443, 2017. Abstract | Links | Tags: Methodology, Twitter, USA @article{Jones2017, title = {Liberal and Conservative Values: What We Can Learn from Congressional Tweets}, author = {Kevin Jones and Sharareh Noorbaloochi and John Jost and Richard Bonneau and Jonathan Nagler and Joshua A Tucker}, url = {https://onlinelibrary.wiley.com/doi/epdf/10.1111/pops.12415}, year = {2017}, date = {2017-01-02}, journal = {Political Psychology}, volume = {39}, number = {2}, pages = {423-443}, abstract = {Past research using self-report questionnaires administered to ordinary citizens demonstrates that value priorities differ as a function of one’s political ideology, but it is unclear whether this conclusion applies to political elites, who are presumably seeking to appeal to very broad constituencies. We used quantitative methods of textual analysis to investigate value-laden language in a collection of 577,555 messages sent from the public Twitter accounts of over 400 members of the U.S. Congress between 2012 and 2014. Consistent with theoretical expectations, we observed that Republican and conservative legislators stressed values of tradition,conformity, and national security (as well as self-direction), whereas Democratic and liberal legislators stressed values of benevolence, universalism, hedonism, and social/economic security (as well as achievement). Implications for the large-scale observational study of political psychology are explored.}, keywords = {Methodology, Twitter, USA}, pubstate = {published}, tppubtype = {article} } Past research using self-report questionnaires administered to ordinary citizens demonstrates that value priorities differ as a function of one’s political ideology, but it is unclear whether this conclusion applies to political elites, who are presumably seeking to appeal to very broad constituencies. We used quantitative methods of textual analysis to investigate value-laden language in a collection of 577,555 messages sent from the public Twitter accounts of over 400 members of the U.S. Congress between 2012 and 2014. Consistent with theoretical expectations, we observed that Republican and conservative legislators stressed values of tradition,conformity, and national security (as well as self-direction), whereas Democratic and liberal legislators stressed values of benevolence, universalism, hedonism, and social/economic security (as well as achievement). Implications for the large-scale observational study of political psychology are explored. |
2016 |
Joshua A Tucker, Jonathan Nagler, Megan Metzger, Duncan Penfold-Brown, Richard Bonneau Big Data, Social Media, and Protest: Foundations for a Research Agenda Book Chapter Alvarez, Michael R (Ed.): Data Analytics in Social Science, Government, and Industry, pp. 199-224, Cambridge University Press, 2016. Links | Tags: Facebook, Protests, Twitter @inbook{Tucker2016, title = {Big Data, Social Media, and Protest: Foundations for a Research Agenda}, author = {Joshua A Tucker and Jonathan Nagler and Megan Metzger and Duncan Penfold-Brown and Richard Bonneau}, editor = {Michael R Alvarez}, doi = {https://doi.org/10.1017/CBO9781316257340.009}, year = {2016}, date = {2016-11-15}, booktitle = {Data Analytics in Social Science, Government, and Industry}, pages = {199-224}, publisher = {Cambridge University Press}, keywords = {Facebook, Protests, Twitter}, pubstate = {published}, tppubtype = {inbook} } |
Jennifer Larson, Jonathan Nagler, Jonathan Ronen, Joshua A Tucker Social Networks and Protest Participation: Evidence from 93 Million Twitter Users Journal Article Political Networks Workshops & Conference 2016, 2016. Abstract | Links | Tags: Charlie Hebdo, Protests, Twitter @article{Larson2016, title = {Social Networks and Protest Participation: Evidence from 93 Million Twitter Users}, author = {Jennifer Larson and Jonathan Nagler and Jonathan Ronen and Joshua A Tucker}, url = {https://ssrn.com/abstract=2796391}, doi = {10.2139/ssrn.2796391}, year = {2016}, date = {2016-06-16}, journal = {Political Networks Workshops & Conference 2016}, abstract = {Pinning down the role of social ties in the decision to protest has been notoriously elusive, largely due to data limitations. The era of social media and its global use by protesters offers an unprecedented opportunity to observe real-time social ties and online behavior, though often without an attendant measure of real-world behavior. We collect data on Twitter activity during the 2015 Charlie Hebdo protests in Paris which, unusually, record both real-world protest attendance and high-resolution network structure. We specify a theory of participation in which an individual’s decision depends on her exposure to others’ intentions, and network position determines exposure. Our findings are strong and consistent with this theory, showing that, relative to comparable Twitter users, protesters are significantly more connected to one another via direct, indirect, triadic, and reciprocated ties. These results offer the first large-scale empirical support for the claim that social network structure influences protest participation. }, keywords = {Charlie Hebdo, Protests, Twitter}, pubstate = {published}, tppubtype = {article} } Pinning down the role of social ties in the decision to protest has been notoriously elusive, largely due to data limitations. The era of social media and its global use by protesters offers an unprecedented opportunity to observe real-time social ties and online behavior, though often without an attendant measure of real-world behavior. We collect data on Twitter activity during the 2015 Charlie Hebdo protests in Paris which, unusually, record both real-world protest attendance and high-resolution network structure. We specify a theory of participation in which an individual’s decision depends on her exposure to others’ intentions, and network position determines exposure. Our findings are strong and consistent with this theory, showing that, relative to comparable Twitter users, protesters are significantly more connected to one another via direct, indirect, triadic, and reciprocated ties. These results offer the first large-scale empirical support for the claim that social network structure influences protest participation. |
Megan Metzger, Joshua A Tucker, Jonathan Nagler, Richard Bonneau Tweeting Identity? Ukrainian, Russian and #EuroMaidan Journal Article The Journal of Comparative Economics, 44 (1), pp. 16-40, 2016. Abstract | Links | Tags: Protests, Twitter, Ukraine @article{Metzger2016, title = {Tweeting Identity? Ukrainian, Russian and #EuroMaidan}, author = {Megan Metzger and Joshua A Tucker and Jonathan Nagler and Richard Bonneau}, url = {https://www.sciencedirect.com/science/article/pii/S0147596715001237?via%3Dihub}, year = {2016}, date = {2016-01-04}, journal = {The Journal of Comparative Economics}, volume = {44}, number = {1}, pages = {16-40}, abstract = {Why and when do group identities become salient? Existing scholarship has suggested that insecurity and competition over political and economic resources as well as increased perceptions of threat from the out-group tend to increase the salience of ethnic identities. Most of the work on ethnicity, however, is either experimental and deals with how people respond once identity has already been primed, is based on self-reported measures of identity, or driven by election results. In contrast, here we examine events in Ukraine from late 2013 (the beginning of the Euromaidan protests) through the end of 2014 to see if particular moments of heightened political tension led to increased identification as either “Russian” or “Ukrainian” among Ukrainian citizens. In tackling this question, we use a novel methodological approach by testing the hypothesis that those who prefer to use Ukrainian to communicate on Twitter will use Ukrainian (at the expense of Russian) following moments of heightened political awareness and those who prefer to use Russian will do the opposite. Interestingly, our primary finding in is a negative result: we do not find evidence that key political events in the Ukrainian crisis led to a reversion to the language of choice at the aggregate level, which is interesting given how much ink has been spilt on the question of the extent to which Euromaidan reflected an underlying Ukrainian vs. Russian conflict. However, we unexpectedly find that both those who prefer Russian and those who prefer Ukrainian begin using Russian with a greater frequency following the annexation of Crimea, thus contributing a whole new set of puzzles – and a method for exploring these puzzles – that can serve as a basis for future research.}, keywords = {Protests, Twitter, Ukraine}, pubstate = {published}, tppubtype = {article} } Why and when do group identities become salient? Existing scholarship has suggested that insecurity and competition over political and economic resources as well as increased perceptions of threat from the out-group tend to increase the salience of ethnic identities. Most of the work on ethnicity, however, is either experimental and deals with how people respond once identity has already been primed, is based on self-reported measures of identity, or driven by election results. In contrast, here we examine events in Ukraine from late 2013 (the beginning of the Euromaidan protests) through the end of 2014 to see if particular moments of heightened political tension led to increased identification as either “Russian” or “Ukrainian” among Ukrainian citizens. In tackling this question, we use a novel methodological approach by testing the hypothesis that those who prefer to use Ukrainian to communicate on Twitter will use Ukrainian (at the expense of Russian) following moments of heightened political awareness and those who prefer to use Russian will do the opposite. Interestingly, our primary finding in is a negative result: we do not find evidence that key political events in the Ukrainian crisis led to a reversion to the language of choice at the aggregate level, which is interesting given how much ink has been spilt on the question of the extent to which Euromaidan reflected an underlying Ukrainian vs. Russian conflict. However, we unexpectedly find that both those who prefer Russian and those who prefer Ukrainian begin using Russian with a greater frequency following the annexation of Crimea, thus contributing a whole new set of puzzles – and a method for exploring these puzzles – that can serve as a basis for future research. |
Cristian Vaccari, Augusto Valeriani, Pablo Barberá, Richard Bonneau, John Jost, Jonathan Nagler, Joshua A Tucker Of Echo Chambers and Contrarian Clubs: Exposure to political disagreement among German and Italian users of Twitter Journal Article Social Media and Society, 2 (3), pp. 1-24, 2016. Links | Tags: Echo Chambers, Elections, Twitter @article{Vaccari2016, title = {Of Echo Chambers and Contrarian Clubs: Exposure to political disagreement among German and Italian users of Twitter}, author = {Cristian Vaccari and Augusto Valeriani and Pablo Barberá and Richard Bonneau and John Jost and Jonathan Nagler and Joshua A Tucker}, url = {http://journals.sagepub.com/doi/full/10.1177/2056305116664221}, year = {2016}, date = {2016-01-02}, journal = {Social Media and Society}, volume = {2}, number = {3}, pages = {1-24}, keywords = {Echo Chambers, Elections, Twitter}, pubstate = {published}, tppubtype = {article} } |
2015 |
Pablo Barberá, Ning Wang, Richard Bonneau, John Jost, Jonathan Nagler, Joshua A Tucker, Sandra Gonzalez-Bailon The Critical Periphery in the Growth of Social Protests Journal Article PLOS One, 2015. Abstract | Links | Tags: Information Flows, Protests, Twitter @article{Barbera2015, title = {The Critical Periphery in the Growth of Social Protests}, author = {Pablo Barberá and Ning Wang and Richard Bonneau and John Jost and Jonathan Nagler and Joshua A Tucker and Sandra Gonzalez-Bailon}, url = {https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0143611}, year = {2015}, date = {2015-11-06}, journal = {PLOS One}, abstract = {Social media have provided instrumental means of communication in many recent political protests. The efficiency of online networks in disseminating timely information has been praised by many commentators; at the same time, users are often derided as “slacktivists” because of the shallow commitment involved in clicking a forwarding button. Here we consider the role of these peripheral online participants, the immense majority of users who surround the small epicenter of protests, representing layers of diminishing online activity around the committed minority. We analyze three datasets tracking protest communication in different languages and political contexts through the social media platform Twitter and employ a network decomposition technique to examine their hierarchical structure. We provide consistent evidence that peripheral participants are critical in increasing the reach of protest messages and generating online content at levels that are comparable to core participants. Although committed minorities may constitute the heart of protest movements, our results suggest that their success in maximizing the number of online citizens exposed to protest messages depends, at least in part, on activating the critical periphery. Peripheral users are less active on a per capita basis, but their power lies in their numbers: their aggregate contribution to the spread of protest messages is comparable in magnitude to that of core participants. An analysis of two other datasets unrelated to mass protests strengthens our interpretation that core-periphery dynamics are characteristically important in the context of collective action events. Theoretical models of diffusion in social networks would benefit from increased attention to the role of peripheral nodes in the propagation of information and behavior.}, keywords = {Information Flows, Protests, Twitter}, pubstate = {published}, tppubtype = {article} } Social media have provided instrumental means of communication in many recent political protests. The efficiency of online networks in disseminating timely information has been praised by many commentators; at the same time, users are often derided as “slacktivists” because of the shallow commitment involved in clicking a forwarding button. Here we consider the role of these peripheral online participants, the immense majority of users who surround the small epicenter of protests, representing layers of diminishing online activity around the committed minority. We analyze three datasets tracking protest communication in different languages and political contexts through the social media platform Twitter and employ a network decomposition technique to examine their hierarchical structure. We provide consistent evidence that peripheral participants are critical in increasing the reach of protest messages and generating online content at levels that are comparable to core participants. Although committed minorities may constitute the heart of protest movements, our results suggest that their success in maximizing the number of online citizens exposed to protest messages depends, at least in part, on activating the critical periphery. Peripheral users are less active on a per capita basis, but their power lies in their numbers: their aggregate contribution to the spread of protest messages is comparable in magnitude to that of core participants. An analysis of two other datasets unrelated to mass protests strengthens our interpretation that core-periphery dynamics are characteristically important in the context of collective action events. Theoretical models of diffusion in social networks would benefit from increased attention to the role of peripheral nodes in the propagation of information and behavior. |
Cristian Vaccari, Augusto Valeriani, Pablo Barberá, Richard Bonneau, John Jost, Jonathan Nagler, Joshua A Tucker Political Expression on Social Media as a Pathway to Engagement: Political Discussion among Twitter Users in Italy Journal Article Journal of Computer-Mediated Communication, 20 (2), pp. 221-239, 2015. Abstract | Links | Tags: Information Flows, Italy, Twitter @article{Vaccari2015, title = {Political Expression on Social Media as a Pathway to Engagement: Political Discussion among Twitter Users in Italy}, author = {Cristian Vaccari and Augusto Valeriani and Pablo Barberá and Richard Bonneau and John Jost and Jonathan Nagler and Joshua A Tucker}, url = {https://onlinelibrary.wiley.com/doi/epdf/10.1111/jcc4.12108}, year = {2015}, date = {2015-01-04}, journal = {Journal of Computer-Mediated Communication}, volume = {20}, number = {2}, pages = {221-239}, abstract = {Scholars and commentators have debated whether lower-threshold forms of political engagement on social media should be treated as being conducive to higher-threshold modes of political participation or a diversion from them. Drawing on an original survey of a representative sample of Italians who discussed the 2013 election on Twitter, we demonstrate that the more respondents acquire political information via social media and express themselves politically on these platforms, the more they are likely to contact politicians via e-mail, campaign for parties and candidates using social media, and attend offline events to which they were invited online. These results suggest that lower-threshold forms of political engagement on social media do not distract from higher-threshold activities, but are strongly associated with them.}, keywords = {Information Flows, Italy, Twitter}, pubstate = {published}, tppubtype = {article} } Scholars and commentators have debated whether lower-threshold forms of political engagement on social media should be treated as being conducive to higher-threshold modes of political participation or a diversion from them. Drawing on an original survey of a representative sample of Italians who discussed the 2013 election on Twitter, we demonstrate that the more respondents acquire political information via social media and express themselves politically on these platforms, the more they are likely to contact politicians via e-mail, campaign for parties and candidates using social media, and attend offline events to which they were invited online. These results suggest that lower-threshold forms of political engagement on social media do not distract from higher-threshold activities, but are strongly associated with them. |
Pablo Barberá, John Jost, Jonathan Nagler, Joshua A Tucker Tweeting From Left to Right: Is Online Political Communication More Than an Echo Chamber? Journal Article Psychological Science, 26 (10), pp. 1531-1542, 2015. Abstract | Links | Tags: Echo Chambers, Twitter @article{Jost2018b, title = {Tweeting From Left to Right: Is Online Political Communication More Than an Echo Chamber?}, author = {Pablo Barberá and John Jost and Jonathan Nagler and Joshua A Tucker}, url = {https://psych.nyu.edu/jost/Tweeting%20from%20Left%20to%20Right_Is%20Online%20Political%20Communication%20More%20Than%20an%20Echo%20Chamber.pdf}, year = {2015}, date = {2015-01-02}, journal = {Psychological Science}, volume = {26}, number = {10}, pages = {1531-1542}, abstract = {We estimated ideological preferences of 3.8 million Twitter users and, using a data set of nearly 150 million tweets concerning 12 political and nonpolitical issues, explored whether online communication resembles an “echo chamber” (as a result of selective exposure and ideological segregation) or a “national conversation.” We observed that information was exchanged primarily among individuals with similar ideological preferences in the case of political issues (e.g., 2012 presidential election, 2013 government shutdown) but not many other current events (e.g., 2013 Boston Marathon bombing, 2014 Super Bowl). Discussion of the Newtown shootings in 2012 reflected a dynamic process, beginning as a national conversation before transforming into a polarized exchange. With respect to both political and nonpolitical issues, liberals were more likely than conservatives to engage in cross-ideological dissemination; this is an important asymmetry with respect to the structure of communication that is consistent with psychological theory and research bearing on ideological differences in epistemic, existential, and relational motivation. Overall, we conclude that previous work may have overestimated the degree of ideological segregation in social-media usage.}, keywords = {Echo Chambers, Twitter}, pubstate = {published}, tppubtype = {article} } We estimated ideological preferences of 3.8 million Twitter users and, using a data set of nearly 150 million tweets concerning 12 political and nonpolitical issues, explored whether online communication resembles an “echo chamber” (as a result of selective exposure and ideological segregation) or a “national conversation.” We observed that information was exchanged primarily among individuals with similar ideological preferences in the case of political issues (e.g., 2012 presidential election, 2013 government shutdown) but not many other current events (e.g., 2013 Boston Marathon bombing, 2014 Super Bowl). Discussion of the Newtown shootings in 2012 reflected a dynamic process, beginning as a national conversation before transforming into a polarized exchange. With respect to both political and nonpolitical issues, liberals were more likely than conservatives to engage in cross-ideological dissemination; this is an important asymmetry with respect to the structure of communication that is consistent with psychological theory and research bearing on ideological differences in epistemic, existential, and relational motivation. Overall, we conclude that previous work may have overestimated the degree of ideological segregation in social-media usage. |
Pablo Barberá Birds of the Same Feather Tweet Together. Bayesian Ideal Point Estimation Using Twitter Data Journal Article Political Analysis, 23 (1), pp. 42-58, 2015. Abstract | Links | Tags: Echo Chambers, Methodology, Twitter @article{Barberá2015, title = {Birds of the Same Feather Tweet Together. Bayesian Ideal Point Estimation Using Twitter Data}, author = {Pablo Barberá}, url = {https://s18798.pcdn.co/smapp/wp-content/uploads/sites/1693/2016/04/paper_barbera.pdf}, year = {2015}, date = {2015-01-01}, journal = {Political Analysis}, volume = {23}, number = {1}, pages = {42-58}, abstract = {Politicians and citizens increasingly engage in political conversations on social media outlets such as Twitter. In this paper I show that the structure of the social networks in which they are embedded can be a source of information about their ideological positions. Under the assumption that social networks are homophilic, I develop a Bayesian Spatial Following model that considers ideology as a latent variable, whose value can be inferred by examining which politics actors each user is following. This method allows us to estimate ideology for more actors than any existing alternative, at any point in time and across many polities. I apply this method to estimate ideal points for a large sample of both elite and mass public Twitter users in the US and five European countries. The estimated positions of legislators and political parties replicate conventional measures of ideology. The method is also able to successfully classify individuals who state their political preferences publicly and a sample of users matched with their party registration records. To illustrate the potential contribution of these estimates, I examine the extent to which online behavior during the 2012 US presidential election campaign is clustered along ideological lines.}, keywords = {Echo Chambers, Methodology, Twitter}, pubstate = {published}, tppubtype = {article} } Politicians and citizens increasingly engage in political conversations on social media outlets such as Twitter. In this paper I show that the structure of the social networks in which they are embedded can be a source of information about their ideological positions. Under the assumption that social networks are homophilic, I develop a Bayesian Spatial Following model that considers ideology as a latent variable, whose value can be inferred by examining which politics actors each user is following. This method allows us to estimate ideology for more actors than any existing alternative, at any point in time and across many polities. I apply this method to estimate ideal points for a large sample of both elite and mass public Twitter users in the US and five European countries. The estimated positions of legislators and political parties replicate conventional measures of ideology. The method is also able to successfully classify individuals who state their political preferences publicly and a sample of users matched with their party registration records. To illustrate the potential contribution of these estimates, I examine the extent to which online behavior during the 2012 US presidential election campaign is clustered along ideological lines. |
2013 |
Cristian Vaccari, Augusto Valeriani, Pablo Barberá, Richard Bonneau, John Jost, Jonathan Nagler, Joshua A Tucker Social Media and Political Communication: A survey of Twitter users during the 2013 Italian general election Journal Article Italian Political Science Review, XLIII (3), pp. 381-410, 2013. Abstract | Links | Tags: Elections, Italy, Twitter @article{Vaccari2013, title = {Social Media and Political Communication: A survey of Twitter users during the 2013 Italian general election}, author = {Cristian Vaccari and Augusto Valeriani and Pablo Barberá and Richard Bonneau and John Jost and Jonathan Nagler and Joshua A Tucker}, url = {https://www.rivisteweb.it/doi/10.1426/75245}, year = {2013}, date = {2013-01-01}, journal = {Italian Political Science Review}, volume = {XLIII}, number = {3}, pages = {381-410}, abstract = {Social media have become increasingly relevant in election campaigns, as both politicians and citizens have integrated them into their communication repertoires. However, little is known about which types of citizens employ these tools to discuss politics and stay informed about current affairs and how they integrate the contents and connections they encounter online with their offline repertoires of political action. In order to address these questions, we devised an innovative online survey involving a random sample representative of Italians who communicated about the 2013 general election on Twitter. Our results show that Twitter political users in Italy are disproportionately male, younger, better educated, more interested in politics, and ideologically more left-wing than the population as a whole. Moreover, there is a strong correlation between online and offline political communication, and Twitter users often relay the political contents they encounter on the web in their face-to-face conversations. Although the political users of social media are not representative of the population, their greater propensity to engage in political conversations both online and offline make them important channels of personal communication and allow the contents that circulate on the web to diffuse among populations that are much broader than those that engage with social media. The electoral significance of these digital platforms thus reaches well beyond the immediate audiences that are exposed to political contents through them.}, keywords = {Elections, Italy, Twitter}, pubstate = {published}, tppubtype = {article} } Social media have become increasingly relevant in election campaigns, as both politicians and citizens have integrated them into their communication repertoires. However, little is known about which types of citizens employ these tools to discuss politics and stay informed about current affairs and how they integrate the contents and connections they encounter online with their offline repertoires of political action. In order to address these questions, we devised an innovative online survey involving a random sample representative of Italians who communicated about the 2013 general election on Twitter. Our results show that Twitter political users in Italy are disproportionately male, younger, better educated, more interested in politics, and ideologically more left-wing than the population as a whole. Moreover, there is a strong correlation between online and offline political communication, and Twitter users often relay the political contents they encounter on the web in their face-to-face conversations. Although the political users of social media are not representative of the population, their greater propensity to engage in political conversations both online and offline make them important channels of personal communication and allow the contents that circulate on the web to diffuse among populations that are much broader than those that engage with social media. The electoral significance of these digital platforms thus reaches well beyond the immediate audiences that are exposed to political contents through them. |
