Empowering NGOs in countering online hate messages

Q1 Social Sciences

Online Social Networks and Media Pub Date : 2021-07-01 DOI:10.1016/j.osnem.2021.100150

Yi-Ling Chung , Serra Sinem Tekiroğlu , Sara Tonelli , Marco Guerini

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引用次数: 8

Abstract

Studies on online hate speech have mostly focused on the automated detection of harmful messages. Little attention has been devoted so far to the development of effective strategies to fight hate speech, in particular through the creation of counter-messages. While existing manual scrutiny and intervention strategies are time-consuming and not scalable, advances in natural language processing have the potential to provide a systematic approach to hatred management. In this paper, we introduce a novel ICT platform that NGO operators can use to monitor and analyse social media data, along with a counter-narrative suggestion tool. Our platform aims at increasing the efficiency and effectiveness of operators’ activities against islamophobia. We test the platform with more than one hundred NGO operators in three countries through qualitative and quantitative evaluation. Results show that NGOs favour the platform solution with the suggestion tool, and that the time required to produce counter-narratives significantly decreases.

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增强非政府组织打击网上仇恨信息的能力

对网络仇恨言论的研究主要集中在有害信息的自动检测上。迄今为止，很少有人关注制定打击仇恨言论的有效战略，特别是通过制造反信息。虽然现有的人工审查和干预策略耗时且不可扩展，但自然语言处理的进步有可能为仇恨管理提供系统的方法。在本文中，我们介绍了一个新的ICT平台，非政府组织运营商可以使用它来监控和分析社交媒体数据，以及一个反叙事建议工具。我们的平台旨在提高经营者反伊斯兰恐惧症活动的效率和效果。我们通过定性和定量的评估，对三个国家的一百多家NGO运营商进行了测试。结果显示，非政府组织倾向于使用建议工具的平台解决方案，并且制作反叙事所需的时间显着减少。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Online Social Networks and Media Social Sciences-Communication

CiteScore

10.60

自引率

0.00%

发文量

审稿时长

44 days