Double bounded rough set, tension measure, and social link prediction

Abstract

The paper describes a new approach of viewing a social relation as a string with various forces acting on it. Accordingly, a tension measure for a relation is defined. Various component forces of the tension measure are identified based on the structural information of the network. A new variant of rough set, namely, double bounded rough set is developed in order to define these forces mathematically. It is revealed experimentally with synthetic and real-world data that positive and negative tension characterize, relatively, the presence and absence of a physical link between two nodes. An algorithm based on tension measure is proposed for link prediction. Superiority of the algorithm is demonstrated on nine real-world networks which include four temporal networks. The source code for calculating tension measure and link prediction algorithm is publicly available at My GitLab.

Publication
IEEE Transactions on Computational Social Systems
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Suman Kundu
Assistant Professor of Computer Science and Engineering

My research interests include social network analysis, network data science, granular computing, soft computing, fuzzy and rough sets.

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