Featuring web communities based on word co-occurrence structure of communications: 736
Featuring web communities based on word co-occurrence structure of communications: 736
复制标题
基于通信词共现结构的网络社区：736
DOI：
10.1145/511446.511542
复制
发表时间：
2002
期刊：
影响因子：
--
通讯作者：
M. Usui
中科院分区：
文献类型：
--
作者：
Y. Ohsawa;H. Soma;Y. Matsuo;N. Matsumura;M. Usui
本文分析了留言板中的文本通信，并对Web社区进行了分类。我们提出了一个通信内容为基础的概括现有的面向业务的分类的Web社区，使用KeyGraph，一种方法，用于可视化文本中的词和词簇之间的共现关系。在这里，在留言板中的文本分析与KeyGraph，并显示所获得的结构，以反映内容流的本质。这种内容流与参与者利益的关系被形式化。参与者和词语之间的关系的三个结构特征，决定了社区的类型，被证明是计算和可视化的：（1）集中，（2）上下文连贯性和（3）创造性的决定。这有助于了解社区的本质，例如社区是否创造有用的知识，加入社区的难易程度，以及社区是否/为什么适合制作商业广告。
Textual communication in message boards is analyzed for classifying Web communities. We present a communication-content based generalization of an existing business-oriented classification of Web communities, using KeyGraph, a method for visualizing the co-occurrence relations between words and word clusters in text. Here, the text in a message board is analyzed with KeyGraph, and the structure obtained is shown to reflect the essence of the content-flow. The relation of this content-flow with participants' interests is then formalized. Three structure-features of relations between participants and words, determining the type of the community, are shown to be computed and visualized: (1) centralization (2) context coherence and (3) creative decisions. This helps in surveying the essence of a community, e.g. whether the community creates useful knowledge, how easy it is to join the community, and whether/why the community is good for making commercial advertisement.