Titlebook: Handbook of Social Network Technologies and Applications; Borko Furht Book 2010 Springer Science+Business Media, LLC 2010 Fuzzy social net

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Modeling Temporal Variation in Social Network: An Evolutionary Web Graph Approachnnected through various social relationships like friendships, kinships, professional, academic etc. Usually, a social network represents a social community, like a club and its members or a city and its citizens etc. or a research group communicating over Internet. In seventies Leinhardt [1] first

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Churn in Social Networksfrom a company’s customer base. There is a simple reason for the attention churn attracts: churning customers mean a loss of revenue. Emerging from business spaces like telecommunications (telcom) and broadcast providers, where churn is a major issue, it is also regarded as a crucial problem in many

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Discovering Mobile Social Networks by Semantic Technologiesrecommendation services, but they realized that the services were not successful. In this chapter, we present semantic technologies for discovering social networks. The process is mainly composed of two steps; (1) profile identification and (2) context understanding. Through developing a Next genera

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Online Identities and Social Networkinging online identities, none has received widespread acceptance. Design and implementation of online identities that are socially acceptable on the Internet remains an open problem. This chapter discusses the interplay between online identities and social networking. Online social networks (OSNs) are

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Detecting Communities in Social Networksorks are important for finding similar people and understanding the structure of factions. This chapter explains the definitions of communities, criteria for evaluating detected communities, methods for community detection, and actual tools for community detection.