Community Structure Identification in Social Networks Inspired by Parliamentary Political Competitions

Abstract

Revealing the concealed community structure, that is vital to understanding the options of networks, is a vital drawback in network and graph analysis. Throughout the last decade, several approaches are projected to resolve this difficult drawback in various ways in which there are totally different measures or knowledge structures. The social network is very popular in the current scenario. Owing to various usefulness in daily routine life, it is a very hot area of research in the current environment. Community structure identification is one of the well-known research works in the social networks. In this research problems are solved by many researchers through different techniques, that is, data mining techniques, soft computing, evolutionary and swarm algorithms. In this experiment, we introduced a novel algorithm called political competition algorithm (PCA) inspired by the Indian parliamentary election procedure. We validate the outcome of the political competition algorithm with the help of various well-known dataset, that is, American Football Club, Books on US Politics, Karate Club and Strike datasets. © 2020, Springer Nature Singapore Pte Ltd.