A system for intergroup prejudice detection: The case of microblogging under terrorist attacks
Autor: | K. Hazel Kwon, H. Raghav Rao, Haimonti Dutta |
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Rok vydání: | 2018 |
Předmět: |
Information Systems and Management
Resentment Microblogging media_common.quotation_subject Internet privacy 02 engineering and technology Anger Management Information Systems Social group Arts and Humanities (miscellaneous) 020204 information systems 0502 economics and business 0202 electrical engineering electronic engineering information engineering Developmental and Educational Psychology Social media media_common business.industry 05 social sciences 16. Peace & justice Terrorism Harassment 050211 marketing Prejudice Psychology business Information Systems |
Zdroj: | Decision Support Systems. 113:11-21 |
ISSN: | 0167-9236 |
DOI: | 10.1016/j.dss.2018.06.003 |
Popis: | 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. |
Databáze: | OpenAIRE |
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