SIAICYHCLGMay 19, 2022

Personalized Interventions for Online Moderation

arXiv:2205.09462v122 citationsh-index: 36
Originality Incremental advance
AI Analysis

This addresses the need for more effective moderation for online platforms, but it is a vision paper without concrete results, so it is incremental in proposing a new direction.

The paper tackles the problem of one-size-fits-all online moderation by proposing a personalized, user-centered approach, aiming to improve effectiveness based on socio-behavioral theories and empirical evidence.

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.

Foundations

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