A Fuzzy Social Network Analysis Method and a Case Study on Tianya Tourism Forum in China [chapter]

Zi Lu, Ruiling Han, Weilu Du, Dianshuang Wu
<span title="">2014</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kax3wwzwmncwhi472pxbzqsjja" style="color: black;">Advances in Intelligent Systems and Computing</a> </i> &nbsp;
Social networking service (SNS) has become online service platforms that focus on facilitating the building of social networks among people who share interests, activities, backgrounds or real-life connections, and has had a rapid development in China in the past few years. This paper aims to develop a fuzzy social network service analysis method, which combines graph-theory with related fuzzy approach, to analyze the social network structural features and the distribution characteristics of
more &raquo; ... erpersonal nodes in SNS community. A case study on a very famous Chinese tourism BBS -Tianya is conducted to illustrate and validate the proposed approach. The research findings are: 1) the attraction degrees of various areas in the forum are significantly different; 2) interpersonal nodes in the forum are concentrated relatively; 3) the fuzzy out-degrees and the fuzzy indegrees of interpersonal nodes in the forum conflict with each other; 4) the distribution of interpersonal nodes is influenced by geographical relations. These findings can directly support social network service management and particularly tourism online service developments. Keywords: Social networking service. Fuzzy systems. Tianya tourism forum. Recently, SNS community researches began to focus on the geographic factors. Lu and Wang [3] applied two methods, namely, information entropy and degree distribution to study the interpersonal node spatial distribution characteristics of SNS community and the significance of geographical factors. Some social network theoretical analysis has also been done. For example, Abbasi et al. [4] developed a theoretical model based on social network theories and analytical methods, using measures from social network analysis (SNA). The social network is a method for quantitative analysis of social relations, which mainly includes two fundamental elements, namely, actors and relations. The nodes of social network graph represent the information mediator and recipients. The arrows indicate the direction of information transfer. The thickness of the connections indicates the frequency of the information transmission or the amount of information transmitted. The overall reflects the statistical features of the information flow between the members of the group. The methods to analyze the social network include: graph-theory method, matrix method, social metrology method, algebraic method, etc. Among these methods, the graph-theory method is suitable for describing the relations in small groups and expressing the structure characteristics of network intuitively. So far, in geographic fields, the graphtheory method has been used in many aspects, such as regional structural characteristics and development direction [5] , inbound tourism flow of network frame and structure features of tourism space [6] . With the in-depth research into the nature of online networking community, it is found that there are non-balanced characteristics in network structure, that is, network consists of several of "nodes" and "connections", and the connections between some nodes are very close while the connections between others are sparse [7] relatively. It is believed that the relationship between actors in social network is fuzzy, and the relationship between actors could not be simply divided into binary relation -"Yes (1)" and "No (0)". Hence, Nair and Sarasamma [8] proposed the definition of fuzzy social networks. They took the nodes and edges in fuzzy graphs as actors and the relationships between actors in social networks respectively, and took that fuzzy social network as a result of giving practical meanings to the fuzzy graph. Ciric and Bogdanovic [9] defined social network as a fuzzy relational structure. They pointed out that the social network is a special case of fuzzy social network. Although social networks has been widely studied, and fuzzy social network has been proposed [10], there are very limited research in
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