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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.
Dr. Niyati Aggrawal is an accomplished and integrity-driven academic professional with over 10 years of rich experience in varied fields of social network analysis, social media mining, information diffusion on social media, web mining techniques and information security. She has guided various graduate projects in the fields of social network analysis and data mining. She has published several research papers in many reputed international journals and conferences related to the above- mentioned research areas. She has actively participated in various conferences, faculty develop-ment programs and workshops. Dr. Adarsh Anand completed his doctorate in the area of Innovation Diffusion Modelling in Marketing and Software Reliability Assessment. Presently, he is working as an assistant professor in the Department of Operational Research, University of Delhi (India). In 2012, he was conferred with the Young Promising Researcher in the field of Technology Management and Software Reliability by Society for Reliability Engineering, Quality and Operations Management (SREQOM). He is a lifetime member of SREQOM. He is also on the editorial board of the International Journal of System Assurance and Engineering Management (Springer). He has guest edited several special issues for journals of international repute. He has edited two books, System Reliability Management (Solutions and Technologies) and Recent Advancements in Software Reliability Assurance, under the banner of Taylor and Francis (CRC Press). He has publications in journals of national and international repute. His research interests include modelling innovation adoption and successive generations in marketing, software reliability growth modelling and social media analysis.
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.
