CLIQUE COMMUNITIES IN SOCIAL NETWORKS

Luís Cavique, Armando B Mendes and Jorge MA Santos

Chapter 19 in Quantitative Modelling in Marketing and Management, 2015, pp 469-490 from World Scientific Publishing Co. Pte. Ltd.

Abstract: There is a pressing need for new pattern recognition tools and statistical methods to quantify large graphs and predict the behaviour of network systems, due to the large amount of data which can be extracted from the web. In this work a graph mining metric, based on k-clique communities, is used, allowing a better understanding of the network structure. The proposed metric shows that for different graph families correspond different k-clique sequences.

Keywords: Quantitative Analysis; Modeling; Marketing Management; Statistical Modelling; Computer Modelling; Memetic Algorithm; Structural Equation Modelling; Artificial Neural Networks (search for similar items in EconPapers)
Date: 2015
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