Community detection and mining in social media
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Author
Contributions
- Liu, Huan - Contributor
Publication
2010 - Morgan & Claypool, San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA), California
Language
English
Word Count
0 words, Guess
Page Count
0 pages
Physical Format
Electronic resource
Identifiers
- Internet Archivecommunitydetecti00tang
- ISBN-139781608453559
- ISBN-139781608453542
- ISBN-101608453553
- ISBN-101608453545
and 3 more
- Better World Books9781608453542
- Better World Books9781608453559
- Open LibraryOL27025199M
Classifications
- DDC006.754
- LCCHM742 .T253 2010
Alternate Titles
- Synthesis digital library of engineering and computer science.
Description
The past decade has witnessed the emergence of participatory Web and social media, bringing people together in many creative ways. Millions of users are playing, tagging, working, and socializing online, demonstrating new forms of collaboration, communication, and intelligence that were hardly imaginable just a short time ago. Social media also helps reshape business models, sway opinions and emotions, and opens up numerous possibilities to study human interaction and collective behavior in an unparalleled scale.This lecture, from a data mining perspective, introduces characteristics of social media, reviews representative tasks of computing with social media, and illustrates associated challenges. It introduces basic concepts, presents state-of-the-art algorithms with easy-to-understand examples, and recommends effective evaluation methods. In particular,we discuss graph-based community detection techniques and many important extensions that handle dynamic, heterogeneous networks in social media. We also demonstrate how discovered patterns of communities can be used for social media mining. The concepts, algorithms, and methods presented in this lecture can help harness the power of social media and support building socially-intelligent systems. This book is an accessible introduction to the study of community detection and mining in social media. It is an essential reading for students, researchers, and practitioners in disciplines and applications where social media is a key source of data that piques our curiosity to understand, manage, innovate, and excel.
Series Statement
- Synthesis lectures on data mining and knowledge discovery -- # 3
Other Editions
- Community detection and mining in social media
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