Elite & Mass Political Behavior

Politicians, celebrities, and other major figures have a big influence on society. They drive conversations, determine policy, and set fashion trends. Our researchers examine the response of political elites to our new media environment, and the impact of social media on political behavior.

Academic Research

  • Journal Article

    How deceptive online networks reached millions in the US 2020 elections

    • Ruth E. Appel, 
    • Young Mie Kim, 
    • Jennifer Pan, 
    • Yiqing Xu, 
    • Ben Nimmo, 
    • Daniel Robert Thomas, 
    • Hunt Allcott, 
    • Pablo Barberá
    • Taylor Brown, 
    • Adriana Crespo-Tenorio, 
    • Drew Dimmery, 
    • Deen Freelon, 
    • Matthew Gentzkow, 
    • Sandra González-Bailón
    • Andrew M. Guess
    • Shanto Iyengar, 
    • David Lazer, 
    • Neil Malhotra, 
    • Devra Moehler, 
    • Brendan Nyhan, 
    • Jaime Settle, 
    • Emily Thorson, 
    • Rebekah Tromble, 
    • Caros Velasco Rivera, 
    • Arjun Wilkins, 
    • Magdalena Wojcieszak
    • Beixian Xiong, 
    • Chad Kiewiet de Jonge, 
    • Annie Franco, 
    • Winter Mason, 
    • Natalie Jomini Stroud, 
    • Joshua A. Tucker

    Nature Human Behaviour (2026)

    View Article View abstract

    Deceptive online networks are coordinated efforts that use identity deception to pursue strategic political or financial goals. During the US 2020 elections, these networks reached at least 37 million Facebook and 3 million Instagram users, representing 15% and 2% of the platforms’ active US adult users, respectively. Only 3 networks out of 49—1 network with explicitly political aims and 2 that appeared to use politics as a lure for profit—were responsible for over 70% of users reached. Notably, accounts unaffiliated with the networks played an important role in facilitating this reach by resharing content the three networks produced. Deceptive networks, regardless of whether their goals were political or financial, reached users who were older, more conservative, more frequently exposed to content from untrustworthy sources, and spent more time on Facebook.

  • Journal Article

    An enriched, multimodal social media dataset of a UK General Election campaign

    Journal of Quantitative Description: Digital Media, 2025

    View Article View abstract

    This article introduces a dataset of all posts by candidates during the 2024 General Election in the United Kingdom with a presence on the X (formerly Twitter) platform. The article relies on a crowd-sourcing innovation in the United Kingdom that, for the first time, provided researchers with early access to a regularly updated candidate list prior to the start of the election. This made it possible to collect real-time data on candidate posts for 1,604 candidates across 53 separate political parties. Additionally, we download and store 53,327 images and 15,982 videos posted within tweets. We enrich the data with the realized vote count and vote share for each candidate as well as text transcripts extracted from the audio of video posts. Overall, the dataset provides a uniquely comprehensive collection of online campaigning material for an election campaign and will be of considerable value to scholars of political communication, elections, and democratic responsiveness. We also analyze the topics and tone — focusing on negativity — across different media formats to identify patterns in the content and style of candidate communication across parties.

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