The spectacular scientific opportunities afforded by the use of social media are readily apparent when we consider the richness and precision of data on participation in elections, protests, riots, and other spontaneous political events. We are constructing comprehensive data sets of incoming and outgoing social media messages using systematically structured formats that are ideally suited to machine learning methods. We plan to integrate information on social network connectivity and a vast array of metadata on individuals and their social contacts. By developing new methods to harvest and combine these data sources effectively, it will be possible to transform the scientific study of social and political attitudes and behavior.
Every time individuals use social media, they leave behind a digital footprint of what was communicated, when it was communicated, and, to whom it was communicated. Typically, such precise estimates of these variables are available only to laboratory investigators working in artificial settings. To our knowledge, no previous research team has successfully used fine-grained social influence data such as these to predict consequential behavioral outcomes, such as attendance at a given protest or rally or the casting of a vote in an election. We are also conducting panel surveys, which are essential for drawing causal inferences about the cognitive and motivational processes whereby social media use facilitates political participation.
Our overarching goal is to forge an interdisciplinary collaboration that examines the impact of social media on political behavior by iterating through stages of model development, testing, refinement, and validation. First, from social psychology and political science we derive fundamental hypotheses about how, why, and when social media affects citizens’ cognitions and motivations with respect to political participation. Second, we express these questions as empirically testable hypotheses derived from behavioral models (e.g., with quantitative response and predictor variables). And third, drawing from biology and computer science we adapt sophisticated computational methods of approximate inference and machine learning (adapting methods developed for the analysis of Systems Biology data) to evaluate our behavioral models using extremely large social media and social network datasets.
Who We Are: The SMaPP Laboratory was co-founded by four Principle Investigators (Rich Bonneau, John Jost, Jonathan Nagler, and Joshua A. Tucker) from Political Science, Psychology, Computer Science and Biology, and also includes contains post-docs, data scientists, graduate research associates and affiliated faculty collaborators. For a full list of SMaPP personnel see our People Page.
SMaPP-Global: See as well the website of SMaPP-Global, an international collection of scholars studying social media and politics affiliated with the SMaPP lab and supported by the NYU Global Institute of Advanced Study. SMaPP-Global holds bi-annual conferences at NYU-NY (in the fall) and at NYU global sites (in the spring).
|NEW: Emotion shapes the diffusion of moralized content in social networks. by William J. Brady, Julian A. Wills, John T. Jost, Joshua A. Tucker, and Jay J. Van Bavel. Proceedings of the National Academy of Sciences|
|Of Echo Chambers and Contrarian Clubs: Exposure to political disagreement among German and Italian users of Twitter”, by Cristian Vaccari, Augusto Valeriani, Pablo Barberá, Richard Bonneau, John T. Jost, Jonathan Nagler, and Joshua A Tucker, Social Media and Society.|
|Liberal and Conservative Values: What We Can Learn from Congressional Tweets
by Kevin L. Jones, Sharareh Noorbaloochi, John T. Jost, Richard Bonneau, Jonathan Nagler, and Joshua A. Tucker, Political Psychology (now available on Early View!)
|Tweetment Effects on the Tweeted: Experimentally Reducing Racist Harassment
by Kevin Munger, Political Behavior
|Tweeting Identity? Ukrainian, Russian and #EuroMaidan
by Megan Metzger, Richard Bonneau, Jonathan Nagler, and Joshua A. Tucker, Journal of Comparative Economics
|Tweeting From Left to Right: Is Online Political Communication More Than an Echo Chamber?
by Pablo Barberá, John T. Jost, Jonathan Nagler, Joshua A. Tucker and Rich Bonneau, Psychological Science
|The critical periphery in the growth of social protests.
by Pablo Barberá, N. Wang, Richard Bonneau, John T. Jost, Jonathan Nagler, and Joshua A. Tucker, and Sandra González-Bailón. (2015). PLoS ONE.
|Political Expression and Action on Social Media: Exploring the Relationship Between Lower-and Higher-Threshold Political Activities Among Twitter Users in Italy
by Cristian Vaccari, Augusto Valeriani, Pablo Barberá, Rich Bonneau, John T. Jost, Jonathan Nagler and Joshua A. Tucker, Journal of Computer-Mediated Communication
|Protest in the Age of Social Media
by Joshua A. Tucker, Megan Metzger, Duncan Penfold-Brown, Richard Bonneau, John T. Jost and Jonathan Nagler, Carnegie Reporter
|Drawing Inferences and Testing Theories with Big Data
by Jonathan Nagler and Joshua Tucker, PS: Political Science and Politics
|Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data
by Pablo Barberá. Political Analysis