Graph based social media analysis

Table of Contents Graphs in Social and Digital Media Alexandros Iosifidis, Nikolaos Tsapanos, and Ioannis Pitas Introduction Dominant Social Networking/Media Platforms Collecting Data from Social Media Sites Social Media Graphs Graph Storage Formats and Visualization Big Data Issues in Social and Digital Media Distributed Computing Platforms Conclusions Bibliography Mathematical Preliminaries: Graphs and Matrices Nikolaos Tsapanos, Alexandros Iosifidis, and Ioannis Pitas Graph Basics Linear Algebra Tools Matrix Decompositions Vector and Matrix Derivatives Bibliography Algebraic Graph Analysis Nikolaos Tsapanos, Anastasios Tefas, and Ioannis Pitas Introduction Spectral Graph Theory Applications of Graph Analysis Random Graph Generation Graph Clustering Graph Matching Random Walks Graph Anomaly Detection Conclusions Bibliography Web Search Based on Ranking Andrea Tagarelli and Santosh Kabbur, and George Karypis Introduction Information Retrieval Background Relevance Beyond the Web Page Text Centrality and Prestige Topic-Sensitive Ranking Ranking in Heterogeneous Networks Organizing Search Results Conclusion Bibliography Label Propagation and Information Diffusion in Graphs Eftychia Fotiadou, Olga Zoidi, and Ioannis Pitas Introduction Graph Construction Approaches Label Inference Methods Diffusion Processes Social Network Diffusion Models Conclusions Bibliography Graph-Based Pattern Classification and Dimensionality Reduction Alexandros Iosifidis and Ioannis Pitas Introduction Notations Unsupervised Methods Supervised Methods Semi-supervised Methods Applications Conclusions Bibliography Matrix and Tensor Factorization with Recommender System Applications Panagiotis Symeonidis Introduction Singular Value Decomposition on Matrices for Recommender Systems Higher Order Singular Value Decomposition (HOSVD) on Tensors A Real Geo-Social System Based on HOSVD Conclusion Bibliography Multimedia Social Search Based on Hypergraph Learning Constantine Kotropoulos Introduction Hypergraphs Game-Theoretic Approaches to Uniform Hypergraph Clustering Spectral Clustering for Arbitrary Hypergraphs Ranking on Hypergraphs Applications Big Data: Randomized Methods for Matrix/Hypermatrix Decompositions Conclusions Acknowledgments Bibliography Graph Signal Processing in Social Media Sunil Narang Motivation Graph Signal Processing (GSP) Applications Conclusions Bibliography Big Data Analytics for Social Networks Brian Baingana, Panagiotis Traganitis, Georgios Giannakis, and Gonzalo Mateos Introduction Visualizing and Reducing Dimension in Social Nets Inference and Imputation on Social Graphs Unveiling Communities in Social Networks Topology Tracking from Information Cascades Conclusion Acknowledgments Bibliography Semantic Model Adaptation for Evolving Big Social Data Nikoletta Bassiou and Constantine Kotropoulos Introduction to Social Data Evolution Latent Model Adaptation Incremental Spectral Clustering Tensor Model Adaptation Parallel and Distributed Approaches for Big Data Analysis Applications to Evolving Social Data Analysis Conclusions Bibliography Big Graph Storage, Processing and Visualization Jaroslav Pokorny and Vaclav Snasel Introduction Basic Notions Big Graph Data Storage Graph Data Processing Graph Data Visualization Conclusions Bibliography Index

Focused on the mathematical foundations of social media analysis, Graph-Based Social Media Analysis provides a comprehensive introduction to the use of graph analysis in the study of social and digital media. It addresses an important scientific and technological challenge, namely the confluence of graph analysis and network theory with linear algebra, digital media, machine learning, big data analysis, and signal processing. Supplying an overview of graph-based social media analysis, the book provides readers with a clear understanding of social media structure. It uses graph theory, particularly the algebraic description and analysis of graphs, in social media studies. The book emphasizes the big data aspects of social and digital media. It presents various approaches to storing vast amounts of data online and retrieving that data in real-time. It demystifies complex social media phenomena, such as information diffusion, marketing and recommendation systems in social media, and evolving systems. It also covers emerging trends, such as big data analysis and social media evolution. Describing how to conduct proper analysis of the social and digital media markets, the book provides insights into processing, storing, and visualizing big social media data and social graphs. It includes coverage of graphs in social and digital media, graph and hyper-graph fundamentals, mathematical foundations coming from linear algebra, algebraic graph analysis, graph clustering, community detection, graph matching, web search based on ranking, label propagation and diffusion in social media, graph-based pattern recognition and machine learning, graph-based pattern classification and dimensionality reduction, and much more. This book is an ideal reference for scientists and engineers working in social media and digital media production and distribution. It is also suitable for use as a textbook in undergraduate or graduate courses on digital media, social media, or social networks.