滥用内容检测的挑战和前沿

Bertie Vidgen, Alex Harris, D. Nguyen, Rebekah Tromble, Scott A. Hale, H. Margetts
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引用次数: 157

摘要

在线滥用内容检测本身就是一项艰巨的任务。它受到了学术界的广泛关注,特别是在计算语言学社区内,并且随着该领域的成熟,性能似乎有所提高。然而,仍然存在相当大的挑战和未解决的前沿问题,涉及技术、社会和道德层面。这些问题限制了滥用内容检测系统的性能、效率和通用性。在本文中,我们描述并澄清了该领域的主要挑战和前沿,批判性地评估了它们的影响,并讨论了潜在的解决方案。我们还强调了社会科学见解可以推动研究的方式。我们讨论了对研究滥用内容的研究人员缺乏支持,并提供了伦理研究的指导方针。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges and frontiers in abusive content detection
Online abusive content detection is an inherently difficult task. It has received considerable attention from academia, particularly within the computational linguistics community, and performance appears to have improved as the field has matured. However, considerable challenges and unaddressed frontiers remain, spanning technical, social and ethical dimensions. These issues constrain the performance, efficiency and generalizability of abusive content detection systems. In this article we delineate and clarify the main challenges and frontiers in the field, critically evaluate their implications and discuss potential solutions. We also highlight ways in which social scientific insights can advance research. We discuss the lack of support given to researchers working with abusive content and provide guidelines for ethical research.
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