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Deep Learning for Social Media Data Analytics (Studies in Big Data)

By: Akrati Saxena (Edited by) , Anupam Biswas (Edited by) , Leticia Serrano-Estrada (Edited by) , Tzung-Pei Hong (Edited by)

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Ksh 29,650.00

Format: Hardback or Cased Book

ISBN-10: 303110868X

ISBN-13: 9783031108686

Collection / Series: Studies in Big Data

Collection Type: Publisher collection

Edition statement: 2022 ed.

Publisher: Springer International Publishing AG

Imprint: Springer International Publishing AG

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Sep 19th, 2022

Publication Status: Active

Product extent: 299 Pages

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This edited book covers ongoing research in both theory and practical applications of using deep learning for social media data. It includes fifteen chapters, organized into four sections that report on original research in network structure analysis, social media text analysis, user behaviour analysis and social media security analysis.

This edited book covers ongoing research in both theory and practical applications of using deep learning for social media data. Social networking platforms are overwhelmed by different contents, and their huge amounts of data have enormous potential to influence business, politics, security, planning and other social aspects. Recently, deep learning techniques have had many successful applications in the AI field. The research presented in this book emerges from the conviction that there is still much progress to be made toward exploiting deep learning in the context of social media data analytics. It includes fifteen chapters, organized into four sections that report on original research in network structure analysis, social media text analysis, user behaviour analysis and social media security analysis. This work could serve as a good reference for researchers, as well as a compilation of innovative ideas and solutions for practitioners interested in applying deep learning techniques to social media data analytics.

 



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