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SOCIAL MEDIA MINING
The growth of social media over the last decade has revolutionized the way individuals interact and industries conduct business. Individuals produce data at an unprecedented rate by interacting, sharing, and consuming con- tent through social media. Understanding and processing this new type of data to glean actionable patterns presents challenges and opportunities for interdisciplinary research, novel algorithms, and tool development. Social Media Mining integrates social media, social network analysis, and data mining to provide a convenient and coherent platform for students, practitioners, researchers, and project managers to understand the basics and potentials of social media mining. It introduces the unique problems arising from social media data and presents fundamental concepts, emerging issues, and effective algorithms for network analysis and data mining. Suitable for use in advanced undergraduate and beginning graduate courses as well as professional short courses, the text contains exercises of different degrees of difficulty that improve understanding and help apply concepts, principles, and methods in various scenarios of social media mining.
Reza Zafarani is a research associate of Computer Science and Engineering at Arizona State University. He performs research in user behavioral mod- eling and was among the first to conduct research on user identification and behavioral analysis across sites.
Mohammad Ali Abbasi is a research associate of Computer Science and Engineering at Arizona State University. His research is focused on evaluat- ing user credibility in social media and using social media for humanitarian assistance and disaster relief.
Huan Liu is a professor of Computer Science and Engineering at Arizona State University where he has been recognized for excellence in teaching and research. His research interests are in data mining, machine learning, social computing, artificial intelligence, and investigating problems that arise in real-world, data-intensive applications with high-dimensional data of disparate forms, such as social media.
i P1: WQS Trim: 6.125in × 9.25in Top: 0.5in Gutter: 0.75in CUUS2079-FM CUUS2079-Zafarani 978 1 107 01885 3 January 14, 2014 17:27
ii P1: WQS Trim: 6.125in × 9.25in Top: 0.5in Gutter: 0.75in CUUS2079-FM CUUS2079-Zafarani 978 1 107 01885 3 January 14, 2014 17:27
SOCIAL MEDIA MINING An Introduction
REZA ZAFARANI Arizona State University, Tempe
MOHAMMAD ALI ABBASI Arizona State University, Tempe
HUAN LIU Arizona State University, Tempe
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www.cambridge.org Information on this title: www.cambridge.org/9781107018853