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WIREs Data Mining Knowl Discov
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Understanding online groups through social media

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Abstract 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

There are a large number groups in online social media. This figure shows the impact from just one social media site, LiveJournal, over 200 groups with some groups involving thousands of individuals. (Figure provided by Xufei Wang.)

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The BlogTracker application categorizes influential bloggers and archives their blog posts. (Screenshot provided by Shamanth Kumar.)

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Group detection, online activities, and sentiment analysis will combine to provide forecasts of group activities in the physical world. (Figure provided by Mohammed Ali Abbasi.)

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Fundamental Concepts of Data and Knowledge > Human Centricity and User Interaction
Algorithmic Development > Web Mining
Fundamental Concepts of Data and Knowledge > Data Concepts

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