Principles of Social Networking: The New Horizon and Emerging Challenges

ISBN-13: 9789811633973 / Angielski / Twarda / 2021 / 468 str.

Anupam Biswas; Ripon Patgiri; Bhaskar Biswas

Spis treści

Centrality Measures : A Tool to Identify Key Actors in Social Networks.- Network Centrality Measures role and importance in Social Networks.- Temporal Network Motifs: Structure roles, Computational issues and its Applications.- Link Prediction on Social Networks based on Centrality Measures.

O autorze

Anupam Biswas received his Ph.D. degree in computer science and engineering from Indian Institute of Technology (BHU), Varanasi, India. He has received his M. Tech. and B. E. Degree in computer science and engineering from Nehru National Institute of Technology Allahabad, Prayagraj, India and Jorhat Engineering College, Jorhat, Assam, India respectively. He is currently working as an Assistant Professor in the Department of Computer Science & Engineering, National Institute of Technology Silchar, Assam. He has published several research papers in reputed international journals, conference and book chapters. His research interests include Social network analysis, Computational music, Machine learning, Fuzzy systems, Information retrieval, and Evolutionary computation. He has served as Program Chair of International Conference on Big Data, Machine Learning and Applications (BigDML 2019).  He is serving as General Chair of 25th International Symposium Frontiers of Research in Speech and Music (FRSM 2020). He is also an editor of multi-authored book, title “Health Informatics: A Computational Perspective in Healthcare“, in the book series of Studies in Computational Intelligence, Springer.

Ripon Patgiri has received his Bachelor Degree from Institution of Electronics and Telecommunication Engineers, New Delhi in 2009. He has received his M.Tech. degree from Indian Institute of Technology Guwahati in 2012. He has received his Doctor of Philosophy from National Institute of Technology Silchar in 2019. After M.Tech. degree, he has joined as Assistant Professor at the Department of Computer Science & Engineering, National Institute of Technology Silchar in 2013. He has published numerous papers in reputed journals, conferences, and books. His research interests include distributed systems, file systems, Hadoop and MapReduce, big data, bloom filter, storage systems, and data-intensive computing. He is a senior member of IEEE. He is a member of ACM and EAI. He is a lifetime member of ACCS, India. Also, he is an associate member of IETE. He was General Chair of 6th International Conference on Advanced Computing, Networking, and Informatics (ICACNI 2018) and International Conference on Big Data, Machine Learning and Applications (BigDML 2019). He is Organizing Chair of 25th International Symposium on Frontiers of Research in Speech and Music (FRSM 2020 and International Conference on Modeling, Simulations and Applications (CoMSO 2020). He is convenor, Organizing Chair and Program Chair of 26th annual International Conference on Advanced Computing and Communications (ADCOM 2020). He is guest editor in special issue “Big Data: Exascale computation and beyond” of EAI Endorsed Transactions on Scalable Information Systems. He is also an editor in a multi-authored book, title “Health Informatics: A Computational Perspective in Healthcare“, in the book series of Studies in Computational Intelligence, Springer. 

Bhaskar Biswas received Ph.D. in Computer Science and Engineering from Indian Institute of Technology(BHU), Varanasi. He received the B.Tech. degree in Computer Science and Engineering from Birla Institute of Technology, Mesra. He is working as Associate Professor at Indian Institute of Technology (BHU), Varanasi in the Computer Science and Engineering department. His research interests include Data Mining,Text Analysis, Machine Learning, Social Network Analysis. He has published several research papers in reputed international journals, conference and book chapters.

Blurb

This book presents new and innovative current discoveries in social networking which contribute enough knowledge to the research community. The book includes chapters presenting research advances in social network analysis and issues emerged with diverse social media data. The book also presents applications of the theoretical algorithms and network models to analyze real-world large-scale social networks and the data emanating from them as well as characterize the topology and behavior of these networks. Furthermore, the book covers extremely debated topics, surveys, future trends, issues, and challenges.