How candidates evoke identity and issues on TikTok

• URL: http://arxiv.org/abs/2509.05310v1
• Date: Tue, 26 Aug 2025 13:27:42 GMT
• Title: How candidates evoke identity and issues on TikTok
• Authors: Sabina Tomkins, Chang Ge, David Rothschild,
• Abstract summary: We examine the final six months before the 2024 US Presidential Election to understand how major campaigns used TikTok.<n>We frame our analysis around two political science theories. The first is the expressive (identity) model, where voters are motivated by their group memberships.<n>We also examine how often candidates attacked opponents, reflecting literature showing attacks are common in politics.
• Score: 2.664168105033125
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Social media platforms are increasingly central to campaign communication, with both paid (advertising) and earned (organic) posts used for fundraising, mobilization, and persuasion. TikTok, and other short-form video platforms, with its short-video format and content-driven algorithms, demand unique content. We examine the final six months before the 2024 US Presidential Election to understand how major campaigns used TikTok. We frame our analysis around two political science theories. The first is the expressive (identity) model, where voters are motivated by their group memberships and candidates appeal to those identities. Alternatively, the instrumental (issues) model argues voters align with politicians advocating their key issues. We also examine how often candidates attacked opponents, reflecting literature showing attacks are common in politics. We combine two datasets: posts from the Harris and Trump campaigns on TikTok (July-November 2024) and a two-wave 2022 survey of around 1,000 respondents. Results show Trump more often disparaged Harris and emphasized identities and issues distinguishing Republicans, while Harris more often highlighted Democratic identities and valued issues. Although issues predict party ID, both candidates referenced identities more (34 percent of posts) than issues (25 percent), with most posts mentioning neither (55 percent).

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