Abstract
In this paper, we introduce a new approach to detect conflicts of interest (COIs) in social networks. We apply this approach to detect COIs in the review process of papers accepted in an international conference that is represented through a social network. This approach consists of extracting some special chains in the studied social network corresponding to conflict of interest cases where the source and target of each chain correspond to an author and a reviewer, respectively. To evaluate the proposed approach, we have conducted some experiments where a comparison with two methods in the literature has been done. The obtained results have shown some efficiency of the proposed approach.
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Albane, S., Slimani, H., Kheddouci, H. (2020). Detection of Conflicts of Interest in Social Networks. In: Cherifi, H., Gaito, S., Mendes, J., Moro, E., Rocha, L. (eds) Complex Networks and Their Applications VIII. COMPLEX NETWORKS 2019. Studies in Computational Intelligence, vol 882. Springer, Cham. https://doi.org/10.1007/978-3-030-36683-4_15
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DOI: https://doi.org/10.1007/978-3-030-36683-4_15
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