A Study of Interactive Structure of Internet Community Using Social Network Analysis – An Example of Fans Page of Facebook

• Main Authors: Wei-Chen Chang, 張瑋晨
• Other Authors: Ho-Chuan Huang
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/6hpc4t

碩士 === 國立高雄應用科技大學 === 資訊管理研究所碩士班 === 102 === In recent years, the internet has enhanced the convenience of communication between people, so that the internet community has become one of the major social channels for modern people. Thus, the interaction models of the internet community members are extraordinarily important. Many factors that may affect the members' interaction in the internet community, includes website features, members' personal characteristics, and so on. Now, Facebook is one of most popular social community, and the interaction between members in social communities produces a variety of interactive structures. Therefore, the purpose of this study was to explore the responding structure of the internet community between originators and repliers. With the analysis of responding structure and social network interaction, different types of social communities will be examined to identify individual social interaction models and discrepancies comparison among them. The records of responding structure and social network indicators were extracted from Facebook fans page, and by using the records of responding structure and social network indicators to discuss the social network interaction further. The result showed that the average in-degree centrality of 3C group's fan page were 9.310 and 9.887, respectively, and the average in-degree centrality of apparel group's fan page were 6.040 and 7.923, respectively. The results also revealed that people were more interested in 3C group's fan page than in apparel group's fan page. The distribution of reply structure illustrated that the wheel's structure was the main structure of trading-based community, and the crisscross's structure was the main structure of interest-based community when the numbers of reply's people are more. Finally, we hope this study can help the operators of internet community to understand the interaction between internet community and replier.