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Social Networks Modelling and Analysis

The goal of this book is to provide a reference for applications of mathematical modelling in social media and related network analysis and offer a theoretically sound background with adequate suggestions for better decision-making. Social Networks: Modelling and Analysis provides the essential knowledge of network analysis applicable to real-world data, with examples from today's most popular social networks such as Facebook, Twitter, Instagram, YouTube, etc. The book provides basic notation and terminology used in social media and its network science. It covers the analysis of statistics for social network analysis such as degree distribution, centrality, clustering coefficient, diameter, and path length. The ranking of the pages using rank algorithms such as Page Rank and HITS are also discussed.   Written as a reference this book is for engineering and management students, research scientists, as well as academicians involved in complex networks, mathematical sciences, and marketing research. Table of Contents 1. Introduction to Social Networks, 2. Network Statistics and Related Concepts. 3. Network Models. 4. Network Centrality. 5. Link Analysis. 6. Link Prediction. 7. Community Detention. 8. Ego Networks. 9. Network Cohesion. 10. Information Diffusion. 11. Security and Privacy in Social Network. 12. Social Network Analysis Tools.

ใส่ตะกร้า
  • ISBN9780367541392
  • ประเภท E-Book
  • ผู้แต่ง Niyati Aggrawal
  • สำนักพิมพ์ CRC Press
  • ครั้งที่พิมพ์ 1
  • ปีที่พิมพ์2022
  • ภาษาภาษาอังกฤษ
  • หมวดหมู่เทคโนโลยีสารสนเทศ / บรรณารักษ์
: ข้อมูลหนังสือ

The goal of this book is to provide a reference for applications of mathematical modelling in social media and related network analysis and offer a theoretically sound background with adequate suggestions for better decision-making. Social Networks: Modelling and Analysis provides the essential knowledge of network analysis applicable to real-world data, with examples from today's most popular social networks such as Facebook, Twitter, Instagram, YouTube, etc. The book provides basic notation and terminology used in social media and its network science. It covers the analysis of statistics for social network analysis such as degree distribution, centrality, clustering coefficient, diameter, and path length. The ranking of the pages using rank algorithms such as Page Rank and HITS are also discussed.   Written as a reference this book is for engineering and management students, research scientists, as well as academicians involved in complex networks, mathematical sciences, and marketing research. Table of Contents 1. Introduction to Social Networks, 2. Network Statistics and Related Concepts. 3. Network Models. 4. Network Centrality. 5. Link Analysis. 6. Link Prediction. 7. Community Detention. 8. Ego Networks. 9. Network Cohesion. 10. Information Diffusion. 11. Security and Privacy in Social Network. 12. Social Network Analysis Tools.