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You Must Be a Trump Supporter: Political Identity Projections on the Social Web

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Social Networks Analysis and Mining (ASONAM 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 15211))

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Abstract

This paper assesses the extent of political polarization in the United States by demonstrating the phenomenon of political identity projection, where individuals attribute political affiliations to others based on political discourse. This aspect of political behavior, often found in interactions between authors on various social media platforms, remains relatively unexplored. To address this gap, our research utilizes a comprehensive dataset of comments on YouTube news videos from three prominent US cable news networks (Fox News, CNN, and MSNBC) to interpret expressions of political polarization. First, we assess the accuracy of LLMs in identifying political identity projections, exploring the potential biases these models may incorporate. Second, we conduct a user engagement analysis that highlights interaction patterns and their implications for understanding political identity projections across different news outlets.

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Notes

  1. 1.

    Publicly available at Github link: .

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Author information

Authors and Affiliations

  1. Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India

    Shubh Mittal & Tisha Chawla

  2. Rochester Institute of Technology, Rochester, NY, 14623, USA

    Ashiqur R. KhudaBukhsh

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  1. Shubh Mittal
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  2. Tisha Chawla
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  3. Ashiqur R. KhudaBukhsh
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Correspondence to Ashiqur R. KhudaBukhsh .

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Editors and Affiliations

  1. IT University of Copenhagen, Copenhagen, Denmark

    Luca Maria Aiello

  2. Indian Institute of Technology Delhi, New Delhi, Delhi, India

    Tanmoy Chakraborty

  3. Università degli Studi di Milano, Milan, Italy

    Sabrina Gaito

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Mittal, S., Chawla, T., KhudaBukhsh, A.R. (2025). You Must Be a Trump Supporter: Political Identity Projections on the Social Web. In: Aiello, L.M., Chakraborty, T., Gaito, S. (eds) Social Networks Analysis and Mining. ASONAM 2024. Lecture Notes in Computer Science, vol 15211. Springer, Cham. https://doi.org/10.1007/978-3-031-78541-2_24

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