CSMaP is a leading academic research institute studying the ever-shifting online environment at scale. We publish peer-reviewed research in top academic journals, produce rigorous reports and analyses on policy relevant topics, and develop open source tools and methods to support the broader scholarly community.

Academic Research

  • Journal Article

    Digital Town Square? Nextdoor's Offline Contexts and Online Discourse

    Journal of Quantitative Description: Digital Media, 2024

    View Article View abstract

    There is scant quantitative research describing Nextdoor, the world's largest and most important hyperlocal social media network. Due to its localized structure, Nextdoor data are notoriously difficult to collect and work with. We build multiple datasets that allow us to generate descriptive analyses of the platform's offline contexts and online content. We first create a comprehensive dataset of all Nextdoor neighborhoods joined with U.S. Census data, which we analyze at the community-level (block-group). Our findings suggests that Nextdoor is primarily used in communities where the populations are whiter, more educated, more likely to own a home, and with higher levels of average income, potentially impacting the platform's ability to create new opportunities for social capital formation and citizen engagement. At the same time, Nextdoor neighborhoods are more likely to have active government agency accounts---and law enforcement agencies in particular---where offline communities are more urban, have larger nonwhite populations, greater income inequality, and higher average home values. We then build a convenience sample of 30 Nextdoor neighborhoods, for which we collect daily posts and comments appearing in the feed (115,716 posts and 163,903 comments), as well as associated metadata. Among the accounts for which we collected posts and comments, posts seeking or offering services were the most frequent, while those reporting potentially suspicious people or activities received the highest average number of comments. Taken together, our study describes the ecosystem of and discussion on Nextdoor, as well as introduces data for quantitatively studying the platform.

    Date Posted

    May 29, 2024

  • Journal Article

    The Effects of Facebook and Instagram on the 2020 Election: A Deactivation Experiment

    • Hunt Alcott, 
    • Matthew Gentzkow, 
    • Winter Mason, 
    • Arjun Wilkins, 
    • Pablo Barberá
    • Taylor Brown, 
    • Juan Carlos Cisneros, 
    • Adriana Crespo-Tenorio, 
    • Drew Dimmery, 
    • Deen Freelon, 
    • Sandra González-Bailón
    • Andrew M. Guess
    • Young Mie Kim, 
    • David Lazer, 
    • Neil Malhotra, 
    • Devra Moehler, 
    • Sameer Nair-Desai, 
    • Houda Nait El Barj, 
    • Brendan Nyhan, 
    • Ana Carolina Paixao de Queiroz, 
    • Jennifer Pan, 
    • Jaime Settle, 
    • Emily Thorson, 
    • Rebekah Tromble, 
    • Carlos Velasco Rivera, 
    • Benjamin Wittenbrink, 
    • Magdalena Wojcieszak
    • Saam Zahedian, 
    • Annie Franco, 
    • Chad Kiewiet De Jong, 
    • Natalie Jomini Stroud, 
    • Joshua A. Tucker

    Proceedings of the National Academy of Sciences, 2024

    View Article View abstract

    We study the effect of Facebook and Instagram access on political beliefs, attitudes, and behavior by randomizing a subset of 19,857 Facebook users and 15,585 Instagram users to deactivate their accounts for 6 wk before the 2020 U.S. election. We report four key findings. First, both Facebook and Instagram deactivation reduced an index of political participation (driven mainly by reduced participation online). Second, Facebook deactivation had no significant effect on an index of knowledge, but secondary analyses suggest that it reduced knowledge of general news while possibly also decreasing belief in misinformation circulating online. Third, Facebook deactivation may have reduced self-reported net votes for Trump, though this effect does not meet our preregistered significance threshold. Finally, the effects of both Facebook and Instagram deactivation on affective and issue polarization, perceived legitimacy of the election, candidate favorability, and voter turnout were all precisely estimated and close to zero.

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Reports & Analysis

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Data Collections & Tools

As part of our project to construct comprehensive data sets and to empirically test hypotheses related to social media and politics, we have developed a suite of open-source tools and modeling processes.