Abstract
This work aims at proposing an original approach based on formal concept analysis (FCA) for community detection in social networks (SN). Firstly, we study FCA methods which partially detect community in social networks. Secondly we propose a GroupNode modularity function whose goal is to improve a partial detection method taking into account all actors of the social network. Our approach is validated through different experiments based on real known social networks in the field and a synthetic benchmark networks. In addition, we adapted the F-measure function in the case of multi-class in order to evaluate the quality of a detected community.
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Ali, S.S., Bentayeb, F., Missaoui, R., Boussaid, O. (2014). An Efficient Method for Community Detection Based on Formal Concept Analysis. In: Andreasen, T., Christiansen, H., Cubero, JC., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2014. Lecture Notes in Computer Science(), vol 8502. Springer, Cham. https://doi.org/10.1007/978-3-319-08326-1_7
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DOI: https://doi.org/10.1007/978-3-319-08326-1_7
Publisher Name: Springer, Cham
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