TY - JOUR
T1 - A system for intergroup prejudice detection
T2 - The case of microblogging under terrorist attacks
AU - Dutta, Haimonti
AU - Kwon, Kyounghee
AU - Rao, H. Raghav
N1 - Funding Information:
The authors would like to thank Sujoy Dutta, Mimanshu Shisodia, Sneha Prabhakar, Sreya Nayak, Nitin Nataraj and Chris Bang for help with empirical analysis and annotation. This research is supported in part by the National Science Foundation under grants - SES-1227353 , SBE-1419856 , 1353119 and 1651475 .
Publisher Copyright:
© 2018
PY - 2018/9
Y1 - 2018/9
N2 - 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.
AB - 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.
KW - Intergroup prejudice detection system
KW - Logistic regression with regularization
KW - Machine learning
KW - Social media text classification
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U2 - 10.1016/j.dss.2018.06.003
DO - 10.1016/j.dss.2018.06.003
M3 - Article
AN - SCOPUS:85048855357
SN - 0167-9236
VL - 113
SP - 11
EP - 21
JO - Decision Support Systems
JF - Decision Support Systems
ER -