Community Structure Analysis From Social Networks
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Community Structure Analysis from Social Networks
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.
Community Structure Analysis from Social Networks
This book addresses social and complex network analysis challenges, exploring social network structures, dynamic networks, and hierarchical communities. Emphasising 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 analysing 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 this area of Community Structure Analysis from Social Network Data.
Analyzing Social Media Networks with NodeXL
Analyzing Social Media Networks with NodeXL offers backgrounds in information studies, computer science, and sociology. This book is divided into three parts: analyzing social media, NodeXL tutorial, and social-media network analysis case studies. Part I provides background in the history and concepts of social media and social networks. Also included here is social network analysis, which flows from measuring, to mapping, and modeling collections of connections. The next part focuses on the detailed operation of the free and open-source NodeXL extension of Microsoft Excel, which is used in all exercises throughout this book. In the final part, each chapter presents one form of social media, such as e-mail, Twitter, Facebook, Flickr, and Youtube. In addition, there are descriptions of each system, the nature of networks when people interact, and types of analysis for identifying people, documents, groups, and events. - Walks you through NodeXL, while explaining the theory and development behind each step, providing takeaways that can apply to any SNA - Demonstrates how visual analytics research can be applied to SNA tools for the mass market - Includes case studies from researchers who use NodeXL on popular networks like email, Facebook, Twitter, and wikis - Download companion materials and resources at https://nodexl.codeplex.com/documentation