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A graph grammar and \(K_{4}\)-type tournament-based approach to detect conflicts of interest in a social network

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Abstract

In this paper, we introduce a new approach based on properties of graph grammars to detect conflicts of interest (COIs) in a field represented in the form of a social network. The approach consists of specializing the adaptive star graph grammar (ASGG) of Drewes et al. (Theor Comput Sci 411:3090–3109, 2010) to express kind of subgraphs that we call \(K_4\)-type tournament graphs, corresponding to COIs, that cannot be generated by the node replacement graph grammar. This approach, called graph grammar and \(K_{4}\)-type tournament-based approach to detect conflicts of interest \((GGK_{4}T-COIs)\), is applied to detect COIs in the review process of papers accepted in an international conference which is represented through a social network. In this contribution, the principle of the used graph grammar is not to consider all the generated language but only subgraphs with some properties (corresponding to special graph queries), which identify parts of the social network representing COIs. For evaluating the performances and the efficiency of our proposition, experimentations have been done by comparing it with concurrent methods in the literature. The obtained results have shown that the approach GG\(K_{4}\)T-COIs performs better than the investigated state-of-the-art approaches in terms of type and number of detected COIs.

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Abbreviations

GG :

Graph grammar

ASGG :

Adaptive star graph grammar

\(T_D\) :

Type of input and manipulated data

\(T_G\) :

Type of generated graph

Z :

Initial graph or axiom

P :

Set of production rules

A :

Set of additional specifications of the productions

NAS :

National Academy of Sciences

FDA :

Food and Drug Administration

COI :

Conflict Of Interest

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Acknowledgements

This work has been sponsored by the General Directorate for Scientific Research and Technological Development, Ministry of Higher Education and Scientific Research (DGRSDT), Algeria. The authors are thankful to the anonymous referees for their valuable suggestions and comments which have helped to improve the quality of the paper and its presentation.

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Authors and Affiliations

  1. LIMED Laboratory, Computer Science Department, University of Bejaia, 06000, Bejaia, Algeria

    Saadia Albane & Hachem Slimani

  2. Université de Lyon, CNRS, Université Lyon 1, LIRIS, UMR5205, 69622, Lyon, France

    Hamamache Kheddouci

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  1. Saadia Albane
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  2. Hachem Slimani
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  3. Hamamache Kheddouci
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Correspondence to Saadia Albane.

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Albane, S., Slimani, H. & Kheddouci, H. A graph grammar and \(K_{4}\)-type tournament-based approach to detect conflicts of interest in a social network. Knowl Inf Syst 63, 497–539 (2021). https://doi.org/10.1007/s10115-020-01525-5

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