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Understanding online groups through social media
Author(s) -
Barbier Geoffrey,
Tang Lei,
Liu Huan
Publication year - 2011
Publication title -
wiley interdisciplinary reviews: data mining and knowledge discovery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.506
H-Index - 47
eISSN - 1942-4795
pISSN - 1942-4787
DOI - 10.1002/widm.37
Subject(s) - categorization , social media , group (periodic table) , data science , social group , computer science , user group , knowledge management , world wide web , sociology , social science , artificial intelligence , chemistry , organic chemistry
Multiple fields including sociology, anthropology, and business are interested in understanding group behavior. Applying data mining techniques to social media can help provide insights into group behavior and divulge a group's characteristics by identifying a group, developing a profile for a group, revealing the sentiment of a group, and detailing a group's composition. The ability to accomplish these tasks has practical business and scientific applications such as understanding customers better and providing new insights into influence propagation, as well as the ability to accurately categorize groups over time. This paper highlights some ongoing research efforts aiming at understanding groups through social media. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 330–338 DOI: 10.1002/widm.37 This article is categorized under: Algorithmic Development > Web Mining Application Areas > Society and Culture Fundamental Concepts of Data and Knowledge > Data Concepts Fundamental Concepts of Data and Knowledge > Human Centricity and User Interaction