Social Media Mining: An Introduction (Reza Zafarani, et al)

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Social Media Mining: An Introduction (Reza Zafarani, et al)

The last ten years have seen a transformation in how people engage with one another and how businesses operate. Through social media interactions, content sharing, and consumption, people generate data at an unparalleled rate.

Interdisciplinary research, new algorithms, and tool creation face problems and opportunities in comprehending and processing this new sort of data to discover patterns that can be put to use.

For students, practitioners, researchers, and project managers to understand the fundamentals and potentials of social media mining, social media mining integrates social media, social network analysis, and data mining. It introduces the particular concerns raised by social media data and provides fundamental ideas, contemporary problems, and efficient network analysis and data mining tools.

The text includes exercises of varying degrees of difficulty that aid in understanding and aid in applying concepts, principles, and methods in various scenarios of social media mining. It is appropriate for use in advanced undergraduate and beginning graduate courses as well as professional short courses.

Ebook Details

About the Authors
  • At Arizona State University, Reza Zafarani works as a research associate in the department of computer science and engineering. He does research on user behavioral modeling and was a pioneer in the fields of user identification and cross-site behavioral analysis.
  • At Arizona State University, Mohammad Ali Abbasi works as a research associate in the department of computer science and engineering. His study focuses on how to assess user credibility in social media and how to use social media for disaster relief and humanitarian aid.
  • Professor of computer science and engineering at Arizona State University, Huan Liu has won awards for his outstanding work in both teaching and research. His areas of interest in the study include social media and other real-world, data-intensive applications with high-dimensional data.
Published Date / Year
(April 28, 2014)
332 pages (est.)
eBook Format
PDF (382 pages, 4.8 MB)

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