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The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory, machine learning, stochastic modelling, user behavior analysis and natural language processing, just to name a few. This text provides an understanding of using such methods and techniques in order to manage practical problems and situations. Trends in Social…mehr

Produktbeschreibung
The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory, machine learning, stochastic modelling, user behavior analysis and natural language processing, just to name a few. This text provides an understanding of using such methods and techniques in order to manage practical problems and situations. Trends in Social Network Analysis: Information Propagation, User Behavior Modelling, Forecasting, and Vulnerability Assessment appeals to students, researchers, and professionals working in the field.
Rezensionen
"This volume is a selective post-proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining. ... The papers are uniformly of high quality and represent a good snapshot of the state of the art in the areas that they discuss. ... The high quality of these carefully revised conference papers makes the volume of interest to researchers specializing in social networks who seek to stay abreast of recent developments." (Computing Reviews, September, 2017)