Online Polarization and Violence in the United States: A Computational Analysis of Viewer Comments on Partisan News Coverage of President Donald Trump’s First Assassination Attempt

Abstract

This study analyzes 15,000 user comments from ideologically distinct news platforms—Fox News (right-leaning), ABC News (left-leaning), and BBC News (centrist)—to investigate how political ideology shapes emotional expression and engagement following the July 2024 assassination attempt on President Donald Trump in Pennsylvania. We examine whether right-leaning comments exhibit elevated anger and hate speech, whether left-leaning comments show greater empathy and positive affect, and how emotional intensity influences engagement metrics such as likes and shares. Using computational science methods, we trace the evolution of emotional tone and toxicity over time, focusing on affective polarization triggered by a high-salience violent event. Our findings reveal that ideological alignment amplifies engagement with congruent emotional content, reinforcing echo chambers and intensifying online hostility. We address gaps in understanding how ideological echo chambers amplify polarized emotions and online hostility following a high-profile violent event, emphasizing the place of emotions in contemporary political communication and digital news consumption.

Keywords

affective polarization partisan media digital news violence computational science news engagement

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