From Notepad AI to Social Media: How Can Text Style Transformation Mitigate Social Harm?

2026-04-29

AI Summary

This study addresses the prevalence of aggressive and emotionally harmful content on social media platforms, where current moderation practices predominantly rely on content removal and often overlook opportunities for communicative repair. To bridge this gap, the authors propose a controllable text style transfer–based writing assistance framework that reformulates toxic comments into neutral and温和 expressions while preserving their original semantic meaning. A novel Emotion Drift Index (EDI) is introduced to quantitatively measure emotional shifts before and after rewriting, enabling effective mitigation of harmful interactions without resorting to simple deletion. Experimental results demonstrate that the proposed approach significantly reduces emotional antagonism and social harm in online discourse while maintaining informational integrity.

Abstract

The rapid proliferation of harmful and emotionally damaging content on social media platforms has intensified concerns regarding societal harm. While content moderation efforts primarily focus on detecting and removing harmful posts, less attention has been given to mitigating harm through stylistic text transformation while preserving semantic meaning. In this paper, we propose a writing-assistance framework that can reduce societal harm by transforming aggressive, toxic, or emotionally harmful comments into softer, more neutral stylistic forms inspired by Notepad AI, a simple AI writing assistant. Rather than censoring or suppressing speech, we apply controlled stylistic modifications to preserve core informational content while reducing emotional intensity and identity-based attacks. We introduce an Emotion Drift Index (EDI) metric to systematically quantify emotional change and evaluate the effectiveness of stylistic rewriting, thereby reducing harmful interactions in online environments.

Problem

• text style transformation
• social harm mitigation
• toxic content
• emotion reduction
• online discourse

Innovation

• text style transformation
• harm mitigation
• Emotion Drift Index
• writing assistance
• social media moderation