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Full Description
This book addresses social and complex network analysis challenges, exploring social network structures, dynamic networks, and hierarchical communities. Emphasizing network structure heterogeneity, including directionality and dynamics, it covers community structure concepts like distinctness, overlap, and hierarchy. The book aims to present challenges and innovative solutions in community structure detection, incorporating diversity into problem-solving. Furthermore, it explores the applications of identified community structures within network analysis, offering insights into social network dynamics.
Investigates the practical applications and uses of community structures identified from network analysis across various domains of real-world networks
Highlights the challenges encountered in analyzing community structures and presents state-of-the-art approaches designed to address these challenges
Spans into various domains like business intelligence, marketing, and epidemics, examining influential node detection and crime within social networks
Explores methodologies for evaluating the quality and accuracy of community detection models
Examines a diverse range of challenges and offers innovative solutions in the field of detecting community structures from social networks
The book is a ready reference for researchers and scholars of Computer Science and Computational Social Systems working in the area of Community Structure Analysis from Social Network Data.
Contents
Understanding and Analyzing Social Networks: Types, Dataset Analysis and Challenges 1. Deciphering Social Networks: Types, Applications, and Analytical Challenges 2. Social Network Analysis: Strategies & Challenges in Data Collection, Representation & Analysis 3. Comparative Study of Open Dataset Repositories for Community Detection and Information Diffusion in Online Social Networks Exploration of Community Detection in Social Networks 4. Community Detection: Exploring Structure and Dynamics 5. Graph Clustering Techniques for Community Detection in Social Networks 6. Semi-supervised and Deep Learning Approaches to Social Network Community Analysis Applications of Community Detection: From Biology to Social Challenges 7. Applications of Community Detection in Biological Networks 8. Influential node detection based on implicit communities 9. Connected Communities: The Role of Social Networks in Pandemic Preparedness and Mitigation 10. Identifying Spread Blockers using Overlapping Community Detection for Pandemic Management 11. Spotting Plagiarism in Academic Social Networks by Community Network Identification
