虛擬社群中誰比較可信任？

Who is More Trustworthy in Virtual Community?

王思峰(Sy-Feng Wang) ； 劉麗萍(Mebel Liu)

《中華心理學刊》 49卷1期 (2007/03) Pp. 1-17

https://doi.org/10.6129/CJP.2007.4901.01

摘要

It is important for participants and owners of virtual communities to find out which participants are trustworthy. However, this challenge has not been adequately addressed in practice and/or in research. Following a well-known tenet that past behavior tends to predict future behavior, we applied social network analysis to examine how participants' past interactions in the MyAV virtual community predict trustworthiness. According to the social network indices derived from a social network matrix, which represents past interactions in the community, we found (1) the ”out-degree centrality” index significantly predicts the competence dimension of trustworthiness (β=0.28, p＜0.01); while the ”in-closeness centrality” index significantly predicts the integrity dimension of trustworthiness (β=0.35, p＜0.01). Foremost, both indices outperform other conventional variables (e.g., frequencies of posting messages in the virtual community) in predicting trustworthiness.

關鍵字

可信任 ； 虛擬社群 ； 社會網絡分析 ； 電子商務

並列摘要

It is important for participants and owners of virtual communities to find out which participants are trustworthy. However, this challenge has not been adequately addressed in practice and/or in research. Following a well-known tenet that past behavior tends to predict future behavior, we applied social network analysis to examine how participants' past interactions in the MyAV virtual community predict trustworthiness. According to the social network indices derived from a social network matrix, which represents past interactions in the community, we found (1) the ”out-degree centrality” index significantly predicts the competence dimension of trustworthiness (β=0.28, p＜0.01); while the ”in-closeness centrality” index significantly predicts the integrity dimension of trustworthiness (β=0.35, p＜0.01). Foremost, both indices outperform other conventional variables (e.g., frequencies of posting messages in the virtual community) in predicting trustworthiness.

並列關鍵字

trustworthiness ； virtual community ； social network analysis ； e-commerce

參考文獻

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Analytic Technologies, available

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