Dr. Shugars’ research in computational communication and political communication examines how the platforms, data, and methods of our modern computational world have fundamentally reshaped the ways in which citizens engage with their societies as well as the ways in which researchers can study this political behavior. Their work extends along three interconnected themes: digital discourse, collaborative reasoning, and methodological validity.
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Individuals increasingly acquire political information from social media, frequently through interpersonal, peer-to-peer conversation. Furthermore, these platforms have fundamentally shifted the speed, modality, and nature of “everyday“ political talk, creating a deep need for both theory-building and computational examination of these platforms and their role in political life. This strand of research therefore aims to better understand how digital tools are used in modern discourse and to build new theory around the unique affordances of these platforms.
Select Publications and Working Papers
Pandemics, Protests, and Publics: Demographic Activity and Engagement on Twitter in 2020
Sarah Shugars, Adina Gitomer, Stefan McCabe, Ryan J. Gallagher, Kenneth Joseph, Nir Grinberg, Larissa Doroshenko, Brooke Foucault Welles, and David Lazer. Journal of Quantitative Description: Digital Media, 1. 2021.
Sustained Amplification of COVID-19 Elites in the United States
Ryan J. Gallagher, Larissa Doroshenko, Sarah Shugars, David Lazer, and Brooke Foucault Welles. Social Media + Society, 2021.
Why Keep Arguing? Predicting Participation in Political Conversations Online
Sarah Shugars and Nick Beauchamp
SAGE Open: Social Media and Political Participation Global Issue, March 2019<
Microblog Conversation Recommendation via Joint Modeling of Topics and Discourse
Xingshan Zeng, Jing Li, Lu Wang, Nick Beauchamp, Sarah Shugars, and Kam-Fai Wong
Proceedings of the North American Chapter of the Association for Computational Linguistics (NAACL), June 2018
Democracies rely upon citizens to reason about their political beliefs and to collectively deliberate about matters of common concern. While the lack of “preference constraint” exhibited by ordinary citizens is frequently taken as evidence that most people are incapable of carrying out these basic democratic responsibilities, there has also been a critical disconnect between political theory and measurement of political beliefs. While typically measured as isolated preferences, political theory suggests that belief systems are best understood as complex and sometimes conflicting networks of group identities, normative principles, facts, and preferences. This line of work therefore leverages modern computational tools to re-examine classic questions of individual and collective reasoning.
Select Publications and Working Papers
Good Decisions or Bad Outcomes? A Model for Group Deliberation on Value-Laden Topics
Sarah Shugars
Communication Methods and Measures, June 2020.
The Structure of Reasoning: Measuring Justification and Preferences in Text
Sarah Shugars, working paper.
Recipient of the 2020 John Sprague Award: Best Paper in Political Networks
Winning on the Merits: The Joint Effects of Content and Style on Debate Outcomes
Lu Wang, Nicholas Beauchamp, Sarah Shugars, and Kechen Qin. Transactions of the Association for Computational Linguistics (TACL), Volume 5, 219-232. 2017.
Games for Civic Renewal
Joshua A. Miller, Sarah Shugars, and Daniel Levine
The Good Society, June 2018.
How the resilience of experts to numeric and linguistic peer information improves collective intelligence
Nick Beauchamp, Sarah Shugars, Briony Swire-Thompson, and David Lazer
Under Review
While computational methods have tremendous potential for behavioral insight, the semi-automated analysis of passively collected human subject data also comes with many important questions about the validity and robustness of these new measures. This line of research therefore builds upon Dr. Shugars’ work in digital discourse and collective reasoning in order to more closely examine key measurement issues in these domains.
Select Publications and Working Papers
(Mis)alignment Between Stance Expressed in Social Media Data and Public Opinion Surveys
Kenneth Joseph, Sarah Shugars, Ryan J. Gallagher, Jon Green, Alexi Quintana Mathé, Zijian An, and David Lazer. Empirical Methods in Natural Language Processing (EMNLP). 2021.
Semantic and Cultural Networks
Sarah Shugars and Sandra González-Bailón. The Sage Handbook of Social Network Analysis (Second Edition). Edited by John McLevey, Peter J. Carrington, and John Scott. Forthcoming.
A Matter of Perspective: Computational Social Science and Researcher Choice
Oxford Handbook of Methodological Pluralism. Under review.
One outstanding path from A to B
Sarah Shugars and Sam V. Scarpino. Nature Physics 17 (4), 540-540. 2021.
Curation Bubbles: Domain Versus URL Level Analyses of News Sharing on Social Media
Jon Green, Stefan McCabe, Sarah Shugars, John Harrington, Hanyu Chwe, Luke Horgan, Shuyang Cao, and David Lazer. Working Paper.