© 2018

Machine Learning Techniques for Online Social Networks

  • Tansel Özyer
  • Reda Alhajj


  • Editors are widely known and well established scholars in social network analysis

  • Covers the link between machine learning techniques and social networks

  • Contains case studies describing how various domains may benefit from online social networks


Part of the Lecture Notes in Social Networks book series (LNSN)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama
    Pages 1-22
  3. Pablo Nicolás Terevinto, Miguel Pérez, Josep Domenech, José A. Gil, Ana Pont
    Pages 45-64
  4. Charalampos Chelmis, Daphney-Stavroula Zois
    Pages 85-113
  5. Shatha Jaradat, Nima Dokoohaki, Mihhail Matskin, Elena Ferrari
    Pages 115-133
  6. Soumya Sarkar, Suhansanu Kumar, Sanjukta Bhowmick, Animesh Mukherjee
    Pages 135-154
  7. John Clements, Babak Farzad, Henryk Fukś
    Pages 173-193
  8. Esra Erdin, Eric Klukovich, Mehmet Hadi Gunes
    Pages 195-218
  9. Kashfia Sailunaz, Tansel Özyer, Jon Rokne, Reda Alhajj
    Pages 219-236

About this book


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. 


graph analysis online social network deep learning data analysis functional cluster extraction

Editors and affiliations

  • Tansel Özyer
    • 1
  • Reda Alhajj
    • 2
  1. 1.Department of Computer EngineeringTOBB University of Economics and TechnologyAnkaraTurkey
  2. 2.Department of Computer ScienceUniversity of CalgaryCalgaryCanada

About the editors

Tansel Özyer is an associate professor of Computer Engineering at TOBB University of Economics and Technology, Turkey. He completed his PhD in Computer Science, University of Calgary. He received his MSc and BSc from Computer Engineering departments of METU and Bilkent University. Research interests are data mining, social network analysis, machine learning, bioinformatics, XML, mobile databases, and computer vision.

Reda Alhajj is a professor in the Department of Computer Science at the University of Calgary. He published over 500 papers in refereed international journals and conferences. He is founding editor in chief of the Springer premier journal “Social Networks Analysis and Mining”, founding editor-in-chief of Springer Series “Lecture Notes on Social Networks”, founding editor-in-chief of Springer journal “Network Modeling Analysis in Health Informatics and Bioinformatics”, founding co-editor-in-chief of Springer “Encyclopedia on Social Networks Analysis and Mining”, founding steering chair of IEEE/ACM ASONAM, and three accompanying symposiums FAB, FOSINT-SI and HI-BI-BI. Dr. Alhajj's research concentrates primarily on data science from management to integration and analysis.

Bibliographic information