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This book concentrates on mining networks, a subfield within data science. Data science uses scientific and computational tools to extract valuable knowledge from large data sets. Once data is processed and cleaned, it is analyzed and presented to support decision making process…
"This approachable book introduces network research in R, walking you through every step of doing social network analysis. Drawing together research design, data collection and data analysis, it explains the core concepts of network analysis in a non-technical way. The book bala…
"This book uses literature as a wrench to pry open social networks and to ask different questions than have been asked about social networks previously. The book emphasizes the story-telling aspect of social networks, as well as the connection between narrative and social networ…
This book uses literature as a wrench to pry open social networks and to ask different questions than have been asked about social networks previously. The book emphasizes the story-telling aspect of social networks, as well as the connection between narrative and social network…
"This book examines the foremost techniques of hidden link predictions in stochastic social networks. It deals, principally, with methods and approaches that involve similarity index techniques, matrix factorization, reinforcement models, graph representations and community dete…
"This book examines the foremost techniques of hidden link predictions in stochastic social networks. It deals, principally, with methods and approaches that involve similarity index techniques, matrix factorization, reinforcement models, graph representations and community dete…
Link prediction is required to understand the evolutionary theory of computing for different social networks. However, the stochastic growth of the social network leads to various challenges in identifying hidden links, such as representation of graph, distinction between spurio…
"This book examines the foremost techniques of hidden link predictions in stochastic social networks. It deals, principally, with methods and approaches that involve similarity index techniques, matrix factorization, reinforcement models, graph representations and community dete…
This book provides a comprehensive introduction to the application of artificial intelligence in social computing, from fundamental data processing to advanced social network computing. To broaden readers understanding of the topics addressed, it includes extensive data and a la…
This book provides a comprehensive introduction to the application of artificial intelligence in social computing, from fundamental data processing to advanced social network computing. To broaden readers understanding of the topics addressed, it includes extensive data and a la…