用于在博客中寻找社区的社会超文本模型

Alvin Chin, M. Chignell
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引用次数: 138

摘要

博客已经成为创建虚拟社区的最新交流媒介,一组博客在讨论共同话题的同时,彼此之间的帖子相互链接。在本文中,我们研究了如何通过互联博客作为一种社会超文本形式来发现社区[14]。我们将McMillan和Chavis的社区意识[26]与网络分析[8,11]相结合,提出了一种检测博客社交网络中社区结构的方法和模型。从模型中,我们通过将社会网络分析[17]中的中心性测量与使用行为调查获得的社区意识测量相结合来测量博客中的社区。然后,我们通过一个独立音乐博客的案例研究来说明这种方法的使用。基于中心性测量,发现社区测量的强度与网络结构很好地一致。尽管案例研究的样本量很小,但一旦根据我们的社会超文本模型校准了社区的结构和衡量标准,社区就可以自动找到并衡量其他博客,而无需进行行为调查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A social hypertext model for finding community in blogs
Blogging has become the newest communication medium for creating a virtual community, a set of blogs linking back and forth to one another's postings, while discussing common topics. In this paper, we examine how communities can be discovered through interconnected blogs as a form of social hypertext [14]. We propose a method and model that detects structures of community in the social network of blogs by integrating McMillan and Chavis' sense of community [26] along with network analysis [8, 11]. From the model, we measure community in the blogs by aligning centrality measures from social network analysis [17] with measures of sense of community obtained using behavioural surveys. We then illustrate the use of this approach with a case study built around an independent music blog. The strength of community measures were found to be well aligned with the network structure, based on centrality measures. Even though the sample size from the case study was small, once the structure and measure of communities are calibrated according to our social hypertext model, communities can be automatically found and measured for other blogs without the need for behavioural surveys.
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