English

Personalized Interventions for Online Moderation

Social and Information Networks 2022-05-20 v1 Artificial Intelligence Computers and Society Human-Computer Interaction Machine Learning

Abstract

Current online moderation follows a one-size-fits-all approach, where each intervention is applied in the same way to all users. This naive approach is challenged by established socio-behavioral theories and by recent empirical results that showed the limited effectiveness of such interventions. We propose a paradigm-shift in online moderation by moving towards a personalized and user-centered approach. Our multidisciplinary vision combines state-of-the-art theories and practices in diverse fields such as computer science, sociology and psychology, to design personalized moderation interventions (PMIs). In outlining the path leading to the next-generation of moderation interventions, we also discuss the most prominent challenges introduced by such a disruptive change.

Keywords

Cite

@article{arxiv.2205.09462,
  title  = {Personalized Interventions for Online Moderation},
  author = {Stefano Cresci and Amaury Trujillo and Tiziano Fagni},
  journal= {arXiv preprint arXiv:2205.09462},
  year   = {2022}
}

Comments

The 33rd ACM Conference on Hypertext and Social Media (HT '22)

R2 v1 2026-06-24T11:22:07.838Z