Towards Effective Counter-Responses: Aligning Human Preferences with Strategies to Combat Online Trolling

TL;DR

This paper explores how aligning human preferences with specific response strategies can effectively mitigate online trolling, promoting healthier online discussions and reducing negative impacts.

Contribution

It introduces a methodology for recommending appropriate counter-responses based on troll types, supported by a dataset linking strategies to human preferences.

Findings

Preferred response strategies vary with troll types

The proposed approach guides constructive discussions

It reduces the negative effects of trolling

Abstract

Trolling in online communities typically involves disruptive behaviors such as provoking anger and manipulating discussions, leading to a polarized atmosphere and emotional distress. Robust moderation is essential for mitigating these negative impacts and maintaining a healthy and constructive community atmosphere. However, effectively addressing trolls is difficult because their behaviors vary widely and require different response strategies (RSs) to counter them. This diversity makes it challenging to choose an appropriate RS for each specific situation. To address this challenge, our research investigates whether humans have preferred strategies tailored to different types of trolling behaviors. Our findings reveal a correlation between the types of trolling encountered and the preferred RS. In this paper, we introduce a methodology for generating counter-responses to trolls by recommending appropriate RSs, supported by a dataset aligning these strategies with human preferences across various troll contexts. The experimental results demonstrate that our proposed approach guides constructive discussion and reduces the negative effects of trolls, thereby enhancing the online community environment.