使用模糊逻辑自动检测书面对话中的小组成员、有影响力的成员、关系和层次
Automatic Detection of Small Groups of Persons, Influential Members, Relations and Hierarchy in Written Conversations Using Fuzzy Logic
摘要：
现在很多数据都是在网上论坛上收集的。关键任务之一是确定这些在线群体的社会结构，例如在一个更大的群体中确定子群体。我们将把个体的分组作为一个分类问题来处理。分类器将基于模糊逻辑。分类器的输入将是语言特征和（个体之间的）关系程度。分类器的输出是个体的分组。我们还采用了一种方法，排名检测到的子组的成员，以确定在每个子组的层次结构。数据从HBO电视节目的电线是用来分析的有效性和实用性的模糊逻辑为基础的方法作为替代方法，经典的统计方法通常用于这些问题。所提出的方法可以自动检测出最有影响力的成员，每个组织的电线与90%的准确率。
英文摘要：
Nowadays a lot of data is collected in online forums. One of the key tasks is to determine the social structure of these online groups, for example the identification of subgroups within a larger group. We will approach the grouping of individual as a classification problem. The classifier will be based on fuzzy logic. The input to the classifier will be linguistic features and degree of relationships (among individuals). The output of the classifiers are the groupings of individuals. We also incorporate a method that ranks the members of the detected subgroup to identify the hierarchies in each subgroup. Data from the HBO television show The Wire is used to analyze the efficacy and usefulness of fuzzy logic based methods as alternative methods to classical statistical methods usually used for these problems. The proposed methodology could detect automatically the most influential members of each organization The Wire with 90% accuracy.
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