A Just and Comprehensive Strategy for Using NLP to Address Online Abuse
David Jurgens | Libby Hemphill | Eshwar Chandrasekharan
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Online abusive behavior affects millions and the NLP community has attempted to mitigate this problem by developing technologies to detect abuse. However, current methods have largely focused on a narrow definition of abuse to detriment of victims who seek both validation and solutions. In this position paper, we argue that the community needs to make three substantive changes: (1) expanding our scope of problems to tackle both more subtle and more serious forms of abuse, (2) developing proactive technologies that counter or inhibit abuse before it harms, and (3) reframing our effort within a framework of justice to promote healthy communities.