Publications

Modeling Political Activism around Gun Debate via Social Media

computational social science political science network science social media

The United States have some of the highest rates of gun violence among developed countries. Yet, there is a disagreement about the extent to which firearms should be regulated. In this study, we employ social media signals to examine the predictors of offline political activism, at both population and individual level. We show that it is possible to classify the stance of users on the gun issue, especially accurately when network information is available. Alongside socioeconomic variables, network information such as the relative size of the two sides of the debate is also predictive of state-level gun policy. On individual level, we build a statistical model using network, content, and psycho-linguistic features that predicts real-life political action, and explore the most predictive linguistic features. Thus, we argue that, alongside demographics and socioeconomic indicators, social media provides useful signals in the holistic modeling of political engagement around the gun debate.

Yelena Mejova, Jisun An, Gianmarco De Francisci Morales, Haewoon Kwak

ACM Transactions on Social Computing, 2022

5+ papers citing this work (Google scholar)

Storm the Capitol: Linking Offline Political Speech and Online Twitter Extra-Representational Participation on QAnon and the January 6 Insurrection

computational social science AI/ML/NLP political science social media online harm

The transfer of power stemming from the 2020 presidential election occurred during an unprecedented period in United States history. Uncertainty from the COVID-19 pandemic, ongoing societal tensions, and a fragile economy increased societal polarization, exacerbated by the outgoing president’s offline rhetoric. As a result, online groups such as QAnon engaged in extra political participation beyond the traditional platforms. This research explores the link between offline political speech and online extra-representational participation by examining Twitter within the context of the January 6 insurrection. Using a mixed-methods approach of quantitative and qualitative thematic analyses, the study combines offline speech information with Twitter data during key speech addresses leading up to the date of the insurrection; exploring the link between Trump’s offline speeches and QAnon’s hashtags across a 3-day timeframe. We find that links between online extra-representational participation and offline political speech exist. This research illuminates this phenomenon and offers policy implications for the role of online messaging as a tool of political mobilization.

Claire Seungeun Lee, Juan Merizalde, John D. Colautti, Jisun An and Haewoon Kwak

Frontiers in Sociology, 2022

Press coverage-PsyPost

35+ papers citing this work (Google scholar)

Populist Supporters on Reddit: A Comparison of Content and Behavioral Patterns Within Publics of Supporters of Donald Trump and Hillary Clinton

computational social science political science social media

We investigate differences along these dimensions on the online forum Reddit by comparing linguistic patterns and content of comments in two subreddits focusing on a populist, Donald Trump (/r/The_Donald), and a center-left politician, Hillary Clinton (/r/hillaryclinton), during the 2016 U.S. presidential election campaign.

Andreas Jungherr, Oliver Posegga, Jisun An

Social Science Computer Review. March 2021.

15+ papers citing this work (Google scholar)

Political Discussions in Homogeneous and Cross-Cutting Communication Spaces

computational social science political science social media

We use Reddit to explore the nature of political discussionsin homogeneous and cross-cutting communication spaces. Inparticular, we develop an analytical template to studyinter-actionandlinguistic patternswithin and between politicallyhomogeneous and heterogeneous communication spaces. Ouranalyses reveal different behavioral patterns in homogeneousand cross-cutting communications spaces.

Jisun An, Haewoon Kwak, Oliver Posegga, Andreas Jungherr

Proceedings of the 13th International AAAI Conference on Web and Social Media (ICWSM), 2019

65+ papers citing this work (Google scholar)