Central Library

Normal view MARC view ISBD view

Probabilistic approaches for social media analysis [electronic resource] : data, community and influence / Kun Yue ... [et al.].

Contributor(s): Yue, Kun.
Material type: materialTypeLabelBookSeries: East China Normal University scientific reports: vol. 11.Publisher: Singapore : World Scientific, 2020Description: 1 online resource (292 p.).ISBN: 9789811207389; 9811207380.Subject(s): Social media -- Data processing | Text processing (Computer science) | Quantitative research -- Statistical methods | Machine learning | Content analysis (Communication) -- Data processingGenre/Form: Electronic books.DDC classification: 302.23/1 Online resources: Access to full text is restricted to subscribers.
Contents:
Introduction -- Adaptive and parallel acquisition of social media data from online big graphs -- A Bayesian network-based approach for incremental learning of uncertain knowledge -- Discovering user similarities in social behavioral interactions based on Bayesian network -- Associative categorization of frequent patterns in social media based on Markov network -- Markov network based latent link discovery and community detection in social behavioral interactions -- Probabilistic inferences of latent entity associations in textual web contents -- Containment of competitive influence spread on social networks -- Locating sources in online social networks via random walk.
Summary: "This unique compendium focuses on the acquisition and analysis of social media data. The approaches concern both the data-intensive characteristics and graphical structures of social media. The book addresses the critical problems in social media analysis, which representatively cover its lifecycle. The must-have volume is an excellent reference text for professionals, researchers, academics and graduate students in AI and databases"--Publisher's website.
    average rating: 0.0 (0 votes)
No physical items for this record

Includes bibliographical references and index.

Introduction -- Adaptive and parallel acquisition of social media data from online big graphs -- A Bayesian network-based approach for incremental learning of uncertain knowledge -- Discovering user similarities in social behavioral interactions based on Bayesian network -- Associative categorization of frequent patterns in social media based on Markov network -- Markov network based latent link discovery and community detection in social behavioral interactions -- Probabilistic inferences of latent entity associations in textual web contents -- Containment of competitive influence spread on social networks -- Locating sources in online social networks via random walk.

"This unique compendium focuses on the acquisition and analysis of social media data. The approaches concern both the data-intensive characteristics and graphical structures of social media. The book addresses the critical problems in social media analysis, which representatively cover its lifecycle. The must-have volume is an excellent reference text for professionals, researchers, academics and graduate students in AI and databases"--Publisher's website.

Mode of access: World Wide Web.

System requirements: Adobe Acrobat reader.

There are no comments for this item.

Log in to your account to post a comment.