Discovering knowledge flow in social network

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Abstract

Social network is regarded as an important communication channel. Recently almost people are using social network such as blog, Twitter and Facebook. With the fast spreading of smartphones, social network plays a crucial role for generating and sharing information. Therefore, we cannot figure out how many information flows and where the information came from. To solve this problem, we proposed a novel idea for understanding social network such as blogosphere. By using the centrality measure which is popularly using in field of the graph theory, we will find key players in a social network; we call these players as an 'influential'. And then, we will test their contribution for information flows. For example, power blogger can easily spread some topic or issues in a network by using their prestige. By using this idea, we may predict a path of information flow. And also, we would discover key person for market strategies. In this paper, we introduced not only our novel approach with detailed explanations but also showed a small part of experimental result for showing the possibility.

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APA

Kim, H. J. (2012). Discovering knowledge flow in social network. In Lecture Notes in Electrical Engineering (Vol. 120 LNEE, pp. 469–477). https://doi.org/10.1007/978-94-007-2911-7_44

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