Data Reports

The NYU Social Media and Political Participation (SMaPP) lab analyzed data shared publicly by Twitter on the activity of the Kremlin-linked “Internet Research Agency” (IRA) to examine whether IRA-operated Twitter accounts spread polarizing or misleading content on social media platforms in an attempt to influence the outcome of the 2016 U.S. presidential election.

Five years after the outbreak of the Syrian civil war, the daily death toll continues to climb, and the massive displacement of civilians has become one of the greatest humanitarian crises in modern history. Social media data provide new insight into how the world watches a humanitarian disaster unfold in real time. In particular, the temporal granularity and networked structure of Twitter data provide key insights into what events grab global attention, how perceptions of refugees shift over time, and whose narratives about refugees gain traction.

Analysis of over 29 million tweets collected at NYU’s Social Media and Political Participation (SMaPP) Lab provides the following insights into the success of the “leave” campaign, the surprising dominance of economic issues in the online debate, and the referendum’s increasingly global audience.

We analyzed 426,717 tweets from the fourth GOP debate, hosted by Fox Business Network and The Wall Street Journal Tuesday night (specifically, those with the hashtags “#gopdebate”, “#fbngopdebate”, or “#RepublicanDebate”). What we found highlights the importance of looking beyond mere “mentions” of names and keywords when studying political discussions on Twitter.

When combined with contextual information that we can infer about the people posting the tweets, we can investigate how different groups (Republicans vs. Democrats, for example) respond to events and whether they are doing so in a supportive or critical way. For the analyses here, we start with a collection of every tweet posted during the third GOP debate that contained one of the associated hashtags – giving us a set of of 404,750 tweets. We then combined the tweets with unique measures of the ideology of the sender of each tweet, derived from the follower networks of each sender.

SMaPP has collected tweets containing ISIS-related keywords that provide new perspective on the impact of ISIS in the global Twittersphere. The collection includes 28,758,083 tweets, or all tweets containing Arabic, transliterated Arabic, or English keywords that reference ISIS positively, negatively, or neutrally between February 3 and July 21, 2015. By observing fluctuations in positive, negative, and neutral ISIS-related tweet volume, language, location, and content over time we can gain a more systematic understanding of the online impact of ISIS’ actions and its social media strategy.

SMaPP has collected tweets containing ISIS-related keywords that provide new perspective on the impact of ISIS in the global Twittersphere. The collection includes 28,758,083 tweets, or all tweets containing Arabic, transliterated Arabic, or English keywords that reference ISIS positively, negatively, or neutrally between February 3 and July 21, 2015. By observing fluctuations in positive, negative, and neutral ISIS-related tweet volume, language, location, and content over time we can gain a more systematic understanding of the online impact of ISIS’ actions and its social media strategy.

SMaPP’s dataset of Tweets related to the Turkish protests now comprises more than 22 million tweets. The study of social media can shed interesting light into the dynamics of information diffusion in the organization of collective action. This is particularly the case when social media, as in the Turkish protests, supplies information that is suppressed by traditional media. Evidence suggests that 15K users sent at least one tweet from Gezi Park, which points at the spillover effects of online activity into offline action.

During the 2013 Italian Parliamentary Elections, a total of 1.1 million tweets in Italian mentioning a set of relevant keywords have been captured since January 18. 182,000 different users have sent at least one tweet (in Italian) about the election. In this report, we present our a summary of our preliminary findings.