Machine Learning Techniques for Online Social Networks

• Corporate Author: SpringerLink (Online service)
• Other Authors: Özyer, Tansel (Editor, http://id.loc.gov/vocabulary/relators/edt), Alhajj, Reda (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: Lecture Notes in Social Networks,
• Subjects: Social sciences-Data processing.; Social sciences-Computer programs.; Data mining.; Social media.; Artificial intelligence.; Computational Social Sciences.; Data Mining and Knowledge Discovery.; Social Media.; Artificial Intelligence.
• Physical Description: VIII, 236 p. 102 illus., 85 illus. in color. online resource.
• ISBN: 9783319899329
• ISSN: 2190-5428
• DOI: 10.1007/978-3-319-89932-9

The book covers tools in the study of online social networks such as machine learning techniques, clustering, and deep learning. A variety of theoretical aspects, application domains, and case studies for analyzing social network data are covered. The aim is to provide new perspectives on utilizing machine learning and related scientific methods and techniques for social network analysis. Machine Learning Techniques for Online Social Networks will appeal to researchers and students in these fields. .