A New Algorithm to Detect and Evaluate Learning Communities in Social Networks: Facebook Groups

Meriem Adraoui, Asmaâ Retbi, Mohammed Khalidi Idrissi, Samir Bennani


This article aims to present a new method of evaluating learners by communities on Facebook groups which based on their interactions. The objective of our study is to set up a community learning structure according to the learners' levels. In this context, we have proposed a new algorithm to detect and evaluate learning communities. Our algorithm consists of two phases. The first phase aims to evaluate learners by measuring their degrees of ‘Safely’. The second phase is used to detect communities. These two phases will be repeated until the best community structure is found. Finally, we test the performance of our proposed approach on five Facebook groups. Our algorithm gives good results compared to other community detection algorithms.


Community detection; evaluation; centrality; social network; safely; learning communities.

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Copyright (c) 2019 meriem adraoui, Asmaâ RETBI RETBI, Mohammed Mohammed KHALIDI IDRISSI, Samir BENNANI

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