Characterizing Network Structure of Anti-Trans Actors on TikTok
Maxyn Leitner, Rebecca Dorn, Fred Morstatter, Kristina Lerman

TL;DR
This study analyzes TikTok's pro- and anti-trans communities, revealing their network structures and content amplification, and introduces a novel classification method to improve detection of trans-related content.
Contribution
It develops a taxonomy and a retrieval-augmented classification pipeline for accurately identifying trans-related sentiment on TikTok, enhancing content moderation capabilities.
Findings
Anti-trans and pro-trans communities have interconnected reply networks.
The classification pipeline improves detection accuracy of trans-related content.
Network analysis shows anti-trans actors target trans individuals extensively.
Abstract
The recent proliferation of short form video social media sites such as TikTok has been effectively utilized for increased visibility, communication, and community connection amongst trans/nonbinary creators online. However, these same platforms have also been exploited by right-wing actors targeting trans/nonbinary people, enabling such anti-trans actors to efficiently spread hate speech and propaganda. Given these divergent groups, what are the differences in network structure between anti-trans and pro-trans communities on TikTok, and to what extent do they amplify the effects of anti-trans content? In this paper, we collect a sample of TikTok videos containing pro and anti-trans content, and develop a taxonomy of trans related sentiment to enable the classification of content on TikTok, and ultimately analyze the reply network structures of pro-trans and anti-trans communities. In…
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Taxonomy
TopicsCaching and Content Delivery
