Mining the network value of customers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 16th international conference on World Wide Web
Social Computing: From Social Informatics to Social Intelligence
IEEE Intelligent Systems
Identifying opinion leaders in the blogosphere
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Identifying the influential bloggers in a community
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Group Recommendation System for Facebook
OTM '08 Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: 2008 Workshops: ADI, AWeSoMe, COMBEK, EI2N, IWSSA, MONET, OnToContent + QSI, ORM, PerSys, RDDS, SEMELS, and SWWS
Modeling and Data Mining in Blogosphere
Modeling and Data Mining in Blogosphere
TwitterRank: finding topic-sensitive influential twitterers
Proceedings of the third ACM international conference on Web search and data mining
Networks: An Introduction
Toward Predicting Collective Behavior via Social Dimension Extraction
IEEE Intelligent Systems
Predicting the Future with Social Media
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Link Mining: Models, Algorithms, and Applications
Link Mining: Models, Algorithms, and Applications
Information provenance in social media
SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
Exploiting vulnerability to secure user privacy on a social networking site
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Group Profiling for Understanding Social Structures
ACM Transactions on Intelligent Systems and Technology (TIST)
Sentiment propagation in social networks: a case study in livejournal
SBP'10 Proceedings of the Third international conference on Social Computing, Behavioral Modeling, and Prediction
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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