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<p>Toxic and antisocial user behavior on social media platforms has received considerable scholarly attention due to its detrimental effects on society. This study takes a holistic perspective on the phenomenon of online toxicity by investigating the impact of local community norms on toxic expression. By using six large-scale datasets, comprising over 500 million Telegram messages collected between 2015 and 2024, we analyze toxic user behavior across multiple chats and languages. We introduce a methodological framework that uses a conformity index to characterize conformist, anti-conformist, and independent behavioral tendencies. Our findings show that most users tend to conform to local normative environments, aligning their toxicity with the toxicity levels of the chats in which they participate. This pattern is consistent across datasets and languages, showing a strong association between community norms and user behavior online. Furthermore, we observe that higher levels of user participation in chats are associated with a stronger tendency toward conformity with the surrounding social contexts. Collectively, these findings contribute to a deeper understanding of toxic online behavior and highlight the importance of contextualized approaches to content moderation.</p>

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From toxicity to conformity: adaptive user behavior to social norms in Telegram communities

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月24日

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  • Lorenzo Alvisi,
  • Victoria Popa,
  • Guglielmo Cola,
  • Serena Tardelli,
  • Maurizio Tesconi

摘要

Toxic and antisocial user behavior on social media platforms has received considerable scholarly attention due to its detrimental effects on society. This study takes a holistic perspective on the phenomenon of online toxicity by investigating the impact of local community norms on toxic expression. By using six large-scale datasets, comprising over 500 million Telegram messages collected between 2015 and 2024, we analyze toxic user behavior across multiple chats and languages. We introduce a methodological framework that uses a conformity index to characterize conformist, anti-conformist, and independent behavioral tendencies. Our findings show that most users tend to conform to local normative environments, aligning their toxicity with the toxicity levels of the chats in which they participate. This pattern is consistent across datasets and languages, showing a strong association between community norms and user behavior online. Furthermore, we observe that higher levels of user participation in chats are associated with a stronger tendency toward conformity with the surrounding social contexts. Collectively, these findings contribute to a deeper understanding of toxic online behavior and highlight the importance of contextualized approaches to content moderation.