Semantic Analysis of Conversations and Fuzzy Logic for the Identification of Behavioral Profiles on Facebook Social Network

Youness Chaabi, Khadija Lekdioui, Mounia Boumediane


In this article we describe a new multi-agent approach for the accompaniment and follow-up of learners (tutoring) in collaborative social networks via network technologies. To assist learners in their collaborative learning process, the system we propose offers the possibility to identify the sociological behavioral’ profile of each learner on the basis of the automatic analysis of the asynchronous textual conversations exchanged between learners.
To achieve our aims, we first describe the sociological profiles that we use in our model. Then, we expose the approach used for the semantic analysis of the messages exchanged (full text), as well as the proposed indicators for the determination of these profiles. After, we present the results of the implementation of the system developed as part of an experiment that we conducted with the students of the Master Program “Software Quality” in the Ibn Tofail University of Kenitra, Morocco. We did indeed obtain very good performances during tests on corpora of messages.


Multi-agent system; Collective Learning; Semantic analysis; social behavior profiles; fuzzy logic; Social Networks

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Copyright (c) 2019 Youness CHAABI, Khadija LEKDIOUI, Mounia BOUMEDIANE

International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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