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

2026-03-23

AI Summary

This study investigates whether discussions surrounding eating disorders (ED) on algorithm-driven short-video platforms such as TikTok can coalesce into authentic communities characterized by strong relational ties. Grounded in social tie strength theory, the research analyzes 43,040 ED-related videos and over 560,000 comments using large-scale content analysis, sentiment computation, and text mining, categorizing ED content into three distinct types: Pro-Recovery, Pro-ED, and ED Experiences. The findings empirically reveal, for the first time, structured patterns of affective interaction on the platform: frequent reciprocal engagement correlates with more positive emotional expression, and the sentiment of initial interactions significantly shapes the tone of long-term relational dynamics. Each content category exhibits distinctive interaction profiles, offering novel insights into the formation mechanisms of digital communities within algorithmically mediated environments.

Technology Category

• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community
• Application Domains: Humanities & Computational Social Science
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction

Application Category

• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content
• Social Networks and Social Media: Analysis of web-mediated communications, communities, and crowds
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

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.

Problem

• tie strength
• algorithmic communities
• emotional dynamics
• online community formation
• short-form video platforms

Innovation

• tie strength
• algorithmic communities
• emotional dynamics
• short-form video
• online community formation