Automatic Detection of Small Groups of Persons, Influential Members, Relations and Hierarchy in Written Conversations Using Fuzzy Logic

French Pope III; Rouzbeh A. Shirvani; Mugizi Robert Rwebangira; Mohamed Chouikha; Ayo Taylor; Andres Alarcon Ramirez; Amirsina Torfi

arXiv · 1610.01720

Automatic Detection of Small Groups of Persons, Influential Members, Relations and Hierarchy in Written Conversations Using Fuzzy Logic

French Pope III·Rouzbeh A. Shirvani·Mugizi Robert Rwebangira·Mohamed Chouikha·Ayo Taylor·Andres Alarcon Ramirez·Amirsina Torfi

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Abstract

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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French Pope III, Rouzbeh A. Shirvani, Mugizi Robert Rwebangira, Mohamed Chouikha, Ayo Taylor, Andres Alarcon Ramirez, Amirsina Torfi. 2016-10-06. Automatic Detection of Small Groups of Persons, Influential Members, Relations and Hierarchy in Written Conversations Using Fuzzy Logic. https://arxiv.org/abs/1610.01720

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