Graph-Based Social Media Analysis

This book provides a comprehensive introduction to the use of graph analysis in the study of social media and digital media. It covers the following topics: graphs in social media, graph theory, algebraic analysis of graphs, graph clustering, diffusion in social media, label propagation in graphs, graphs in pattern recognition and machine learning, tensors in graph analysis, recommendation systems based on hypergraphs, big data approaches for social media and graph clustering and graph-based approaches for evolving social data.

Prof. Ioannis Pitas (IEEE fellow, IEEE Distinguished Lecturer, EURASIP fellow) earned his PhD degree from the Department of Electrical Engineering, Aristotle University of Thessaloniki, Greece. He has been a Professor at the Department of Informatics at the same university since 1994 and has served as a visiting professor at several universities.

His current interests are in the areas of intelligent digital media, image/video processing, machine learning, and human-centered computing. He has published over 800 papers, contributed in 44 books in his areas of interest, and edited or co-authored another 10 books. He has also been a member of the program committee of many scientific conferences and workshops. In the past, he has served as an associate editor or co-editor of eight international journals and was General or Technical Chair of four international conferences. He participated in 68 R&D projects, primarily funded by the European Union and is/was principal investigator/researcher in 40 such projects. He has 20600+ citations to his work and h-index 67+ (2015).