Description
Taylor and Francis Social Network Analysis Interdisciplinary Approaches And Case Studies 2017 Edition by Xiaoming Fu, Jar-Der Luo, Margarete Boos
The book addresses the issue of interdisciplinary understanding of collaboration on the topic of social network studies. Researchers and practitioners from various disciplines including sociology, computer science, socio-psychology, public health, complex systems, and management science have worked largely independently, each with quite different principles, terminologies, theories. and methodologies. The book aims to fill the gap among these disciplines with a number of the latest interdisciplinary collaboration studies. PrefaceChapter 1 - Methods for Interdisciplinary Social Network StudiesChapter 2 - Reflectsion on Initial Experiences with Transdisciplinary Engagement between Computer Science and the Social SciencesChapter 3 - How Much Sharing is Enough? Cognitive Patters in Interdisciplinary CollaborationsChapter 4 - The Measurement of Guanxi Circles - Using Qualitative Study to Modify Quantitative Measurement Chapter 5 - Analysis and Prediction of Triadic Closure in Online Social Networks Chapter 6 - The Prediction of Venture Capital Co-Investment Based on Structural Balance Theory Chapter 7 - Repeated Cooperation Matters - An Analysis of Syndication in the Chinese VC Industry by ERGM Model Chapter 8 - Patterns of Group Movement on a Virtual Playfield - Empirical and Simulation ApproachesChapter 9 - Social Spammer and Spam Message Detection in an Online Social Network - A Co-Detection Approach via Exploiting Social ContextsChapter 10 - Cultural Anthropology through the Lens of Wikipedia Chapter 11 - From Social Networks to Time Series: Metho9ds and ApplicationsChapter 12 - How Do Online Social Networks Grow?Chapter 13 - Information Dissemination in Social-Featured Opportunistic NetworksChapter 14 - Sources of Information and Behavioural Patterns in Health Online For aChapter 15 - Mining Big Data for Analyzing and Simulating Collaboration Factors Influencing Software Development Decisions