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Fuzzy Soft Social Network Modeling and Marketing
Abstract
Facebook, Linkedin, Myspace, and other social networks have become a very important environment in which people interact, exchange information about products, services, movies and music, and so forth. New trends and hot items rapidly move through these networks. Clearly, modern marketing has to focus on the possibilities of taking advantage of these networks. The determination of people who are leaders and trendsetters within a social network would be a great benefit for marketing. In recent papers, the authors have developed a model of social networks based on the use of fuzzy set theory and other soft granular computing technologies. This is called the Framework for Intelligent Social Network Analysis (FISNA). Using granular computing, the authors express concepts associated with social networks in a human-focused manner. Since human beings predominantly use linguistic terms in order to communicate, reason, and understand, they are able to build bridges between human conceptualization and the formal mathematical representation of the social networks. Consider, for example, a concept such as “leader.” An analyst may be able to express, in linguistic terms, using a network relevant vocabulary, the properties of a leader. The authors’ framework enables translation of this linguistic description into a mathematical formalism that allows for determination of how true it is that a particular person, a node in the network, is a leader. The authors use fuzzy set methodologies, and more generally granular computing, to provide the necessary bridge between the human analyst and the formal model of the network. In this chapter, the authors investigate and describe the use of the FISNA technology to help in the modeling of market related concepts in social networks.
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