Echoes of Emotion

Influencers’ Communication Strategies and Comment Polarization in the US 2024 Presidential Election

Bibliographic Data

ID17823254
AuthorsXianquan Zeng (corresponding author), Jiarun Du, Jinghong Xu (0000-0003-4654-0603), Qiong Xu (0000-0002-0103-8081)
Year2026
Volume14
Publication date2026-04-30
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueMedia and Communication (JOURNAL)
Journal identifiersISSN: 2183-2439 • E-ISSN: 2183-2439
PublisherCogitatio (PUBLISHER • PT)
DOI10.17645/mac.11794
OpenAlexW7159970525
LanguageEN
Citations received1
References cited56

This study examines strategic differences between Democratic and Republican YouTube influencers during the 2024 US presidential election and their association with comment-level political polarization. Drawing on digital opinion leadership theory, platform architecture perspectives, and visual framing research, we employ a mixed-methods design integrating framing analysis with latent Dirichlet allocation topic modeling. The study analyzes 373 videos and 371,124 comments posted by 40 YouTube influencers (≥100,000 subscribers) from July 27th to November 30th, 2024. Findings reveal that Democratic creators adopted a moral-crisis framing strategy while Republicans emphasized an opportunity–explanation framing model, and that 56.4% of comment discourse centers on candidate personality rather than policy substance, exhibiting patterns consistent with affective polarization. The study develops and empirically calibrates the YouTube polarization risk assessment scale through ordinary least squares regression analysis ( R 2 = 0.224, p < 0.001), identifying political stance strength and humor/sarcasm as the strongest predictors of comment polarization, thereby providing an exploratory, empirically informed framework for assessing polarization risk in platform-based political communication

Democracy · General election · Influencer marketing · Politics · Presidential election · Presidential system · Humor Studies and Applications · Misinformation and Its Impacts · Sentiment Analysis and Opinion Mining

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