Compensatory fuzzy logic for intelligent social network analysis

Maikel Leyva Vázquez, Rafael Bello-Lara, Rafael Alejandro Espín-Andrade

Resumen


Fuzzy graph theory has gained in visibility for social network analysis. In this work fuzzy logic and their role in modeling social relational networks is discussed. We present a proposal for extending the fuzzy logic framework to intelligent social network analysis using the good properties of robustness and interpretability of compensatory fuzzy logic. We apply this approach to the concept path importance taking into account the length and strength of the connection. Additionally a case study to illustrate the applicability of the proposal based on a coauthorship network inside the Eureka network is developed. Our main outcome is a new model for social network analysis based on compensatory fuzzy logic that gives more robust results and allows compensation. The paper ends with conclusion and future research directions.


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La Universidad de las Ciencias Informáticas (UCI), a través del sello editorial Ediciones Futuro, publica los contenidos de la Revista Cubana de Ciencias Informáticas (RCCI) bajo licencia Creative Commons de tipo Atribución 4.0 Internacional (CC BY 4.0). Esta licencia permite a otros distribuir, mezclar, ajustar y construir a partir de su obra, incluso con fines comerciales, siempre que le sea reconocida la autoría de la creación original.
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