Automatic Detection of Small Groups of Persons, Influential Members, Relations and Hierarchy in Written Conversations Using Fuzzy Logic
October 06, 2016 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
French Pope, Rouzbeh A. Shirvani, Mugizi Robert Rwebangira, Mohamed Chouikha, Ayo Taylor, Andres Alarcon Ramirez, Amirsina Torfi
arXiv ID
1610.01720
Category
cs.CL: Computation & Language
Cross-listed
cs.SI
Citations
3
Venue
arXiv.org
Last Checked
5 months ago
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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