Social Networks and Social Information Sharing Using Fuzzy Methods

Abstract

Web 2.0 has provided for a rapid growth of computer mediated social networks. Social relational networks are becoming an important technology in human behavioral modeling. Our goal here is to enrich the domain of social network modeling by introducing ideas from fuzzy sets and related granular computing technologies. We approach this extension in a number of ways. One is with the introduction of fuzzy graphs representing the networks. This allows a generalization of the types of connection between nodes in a network from simply connected or not to weighted or fuzzy connections. A second and perhaps more interesting extension is the use of the fuzzy set based paradigm of computing with words to provide a bridge between a human network analyst’s linguistic description of social network concepts and the formal model of the network. We also will describe some methods for sharing information obtained in these types of networks. In particular we discuss linguistic summarization and tagging methods.