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

被引：0

作者：

Mittal, Shubh ^{[1
]}

Chawla, Tisha ^{[1
]}

KhudaBukhsh, Ashiqur R. ^{[2
]}

机构：

[1] Vellore Inst Technol, Vellore 632014, Tamil Nadu, India

[2] Rochester Inst Technol, Rochester, NY 14623 USA

来源：

SOCIAL NETWORKS ANALYSIS AND MINING, ASONAM 2024, PT I | 2025年 / 15211卷

关键词：

Political Identity Projections; Large Language Models; Social Web; FOX NEWS; POLARIZATION; ATTITUDES; OPINION; MEDIA;

D O I：

10.1007/978-3-031-78541-2_24

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper contains offensive content. 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.

引用

页码：391 / 404

页数：14

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