A system for intergroup prejudice detection: The case of microblogging under terrorist attacks
A system for intergroup prejudice detection: The case of microblogging under terrorist attacks
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DOI：
10.1016/j.dss.2018.06.003
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发表时间：
2018-09-01
影响因子：
7.5
通讯作者：
Rao, H. Raghav
中科院分区：
文献类型：
--
作者：
Dutta, Haimonti;Kwon, K. Hazel;Rao, H. Raghav
群体间偏见是指一个社会群体在不考察事实的情况下对另一个社会群体持有的一种扭曲的观点。在危机或威胁期间，它会得到加强。当一群人对另一个人表达愤怒、怨恨和异议时，它会在社交媒体平台上得到表达。本文提出了一种自动检测社交媒体提要中偏见信息的系统。它使用知识发现框架对数据进行预处理，生成理论驱动的语言特征，以及从文本内容设计的其他特征，注释和建模历史数据，以确定驱动群体间偏见检测的因素，特别是在危机期间。它在波士顿马拉松爆炸事件期间收集的推特上进行了测试。该系统可以通过及时发现和报告群体间偏见来遏制滥用和骚扰。
Intergroup prejudice is a distorted opinion held by one social group about another, without examination of facts. It is heightened during crises or threat. It finds expression in social media platforms when a group of people express anger, resentment and dissent towards another. This paper presents a system for automated detection of prejudiced messages from social media feeds. It uses a knowledge discovery framework that preprocesses data, generates theory-driven linguistic features along with other features engineered from textual content, annotates and models historical data to determine what drives detection of intergroup prejudice especially during a crisis. It is tested on tweets collected during the Boston Marathon bombing event. The system can be used to curb abuse and harassment by timely detection and reporting of intergroup prejudice.