Tied In on TikTok: Tie Strength and Emotional Dynamics in Algorithmic Communities

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Hauptverfasser: Bickham, Charles, Chu, Minh Duc, Yuan, Arianna, Lookingbill, Valerie, Mohammadi, Ehsan, Murray, Stuart, Lerman, Kristina, Ferrara, Emilio
Format: Preprint
Veröffentlicht: 2026
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author Bickham, Charles
Chu, Minh Duc
Yuan, Arianna
Lookingbill, Valerie
Mohammadi, Ehsan
Murray, Stuart
Lerman, Kristina
Ferrara, Emilio
author_facet Bickham, Charles
Chu, Minh Duc
Yuan, Arianna
Lookingbill, Valerie
Mohammadi, Ehsan
Murray, Stuart
Lerman, Kristina
Ferrara, Emilio
contents Whether genuine communities can form on algorithmically-driven short-form video platforms like TikTok remains an open question, given that user interactions are often brief, dispersed, and difficult to trace. Building on theories of tie strength and online community formation, we examine whether eating disorder (ED) discourse on TikTok exhibits behavioral and emotional signatures of strong ties, including more frequent, reciprocal, and affectively intense interactions. In this paper, we analyze 43,040 ED-related TikTok videos and over 560,000 comments, alongside a Non-ED comparison dataset. We find that at the user-pair level, greater interaction frequency is associated with increasingly positive emotional expression, a pattern that is amplified in ED-related conversations. This trend is also reflected linguistically, with pairs that interact more frequently exhibiting more of a positive tone. At the same time, how a relationship starts matters: pairs that begin with positive exchanges usually stay mostly positive as they continue interacting, while pairs that begin negatively may add some positive exchanges over time but rarely become mostly positive. To contextualize these dynamics, we classify ED videos into three content types (Pro-Recovery, Pro-ED, and ED Experiences) and find that each exhibits distinct emotional interaction patterns. These findings suggest that dense, emotionally structured relationships can emerge within ED discourse on TikTok. More broadly, our work provides one of the first empirical demonstrations of how community-like relational dynamics form and persist on algorithmically driven short-form video platforms.
format Preprint
id arxiv_https___arxiv_org_abs_2603_22504
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Tied In on TikTok: Tie Strength and Emotional Dynamics in Algorithmic Communities
Bickham, Charles
Chu, Minh Duc
Yuan, Arianna
Lookingbill, Valerie
Mohammadi, Ehsan
Murray, Stuart
Lerman, Kristina
Ferrara, Emilio
Social and Information Networks
Whether genuine communities can form on algorithmically-driven short-form video platforms like TikTok remains an open question, given that user interactions are often brief, dispersed, and difficult to trace. Building on theories of tie strength and online community formation, we examine whether eating disorder (ED) discourse on TikTok exhibits behavioral and emotional signatures of strong ties, including more frequent, reciprocal, and affectively intense interactions. In this paper, we analyze 43,040 ED-related TikTok videos and over 560,000 comments, alongside a Non-ED comparison dataset. We find that at the user-pair level, greater interaction frequency is associated with increasingly positive emotional expression, a pattern that is amplified in ED-related conversations. This trend is also reflected linguistically, with pairs that interact more frequently exhibiting more of a positive tone. At the same time, how a relationship starts matters: pairs that begin with positive exchanges usually stay mostly positive as they continue interacting, while pairs that begin negatively may add some positive exchanges over time but rarely become mostly positive. To contextualize these dynamics, we classify ED videos into three content types (Pro-Recovery, Pro-ED, and ED Experiences) and find that each exhibits distinct emotional interaction patterns. These findings suggest that dense, emotionally structured relationships can emerge within ED discourse on TikTok. More broadly, our work provides one of the first empirical demonstrations of how community-like relational dynamics form and persist on algorithmically driven short-form video platforms.
title Tied In on TikTok: Tie Strength and Emotional Dynamics in Algorithmic Communities
topic Social and Information Networks
url https://arxiv.org/abs/2603.22504