FIRE 2022的HASOC子轨道概述:英语和印度雅利安语言中的仇恨言论和攻击性内容识别

Thomas Mandl, Sandip J Modha, Gautam Kishore Shahi, Hiren Madhu, Shrey Satapara, Prasenjit Majumder, Johannes Schäfer, Tharindu Ranasinghe, Marcos Zampieri, D. Nandini, A. Jaiswal
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引用次数: 83

摘要

近年来,网络攻击性内容的传播引起了人们的极大关注,这促使研究人员开发出能够自动识别此类内容的强大系统。为了对这些系统进行公平的评估,已经组织了几个国际共享任务,为社区提供了各种语言的基本基准数据和评估方法。自2019年组织以来,HASOC(仇恨言论和冒犯性内容识别)共享任务就是这些举措之一。在其第四次迭代中,HASOC 2022包含了英语-印地语代码组合、德语和马拉地语的三个任务。任务1和任务2是关于会话仇恨言论检测。这个想法是根据推特帖子的周围环境来检测支持仇恨言论、亵渎或其他形式的冒犯。任务1以印地语-英语代码组合和德语提供。任务2是为印地语-英语codemix提供的,它的重点是进一步将会话仇恨言论中的问题推文分类为独立仇恨和上下文仇恨。本文简要介绍了任务、数据和参与。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Overview of the HASOC Subtrack at FIRE 2022: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages
In recent years, the spread of online offensive content has become of great concern, motivating researchers to develop robust systems capable of identifying such content automatically. To carry out a fair evaluation of these systems, several international shared tasks have been organized, providing the community with essential benchmark data and evaluation methods for various languages. Organized since 2019, the HASOC (Hate Speech and Offensive Content Identification) shared task is one of these initiatives. In its fourth iteration, HASOC 2022 included three tasks for English-Hindi codemix, German and Marathi. Tasks 1 and 2 were on conversational hate speech detection. The idea is to detect supporting hate speech, profanity, or other forms of offensiveness depending on the surrounding context of Twitter posts. Task 1 was offered in Hindi-English codemix and German. Task 2 was provided for Hindi-English codemix, and it was focused on further classifying the problematic tweets in conversational hate speech into standalone and contextual hate. This paper presents a brief description of tasks, data, and participation.
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