Métodos de detección de comunidad en redes híbridas aplicado al análisis de redes académicas

Abstract

The characteristics of the multi-node and multi-relationship hybrid network are mainly reflected in the following two aspects: first, the diversity of nodes, including a variety of node types and, second, the richness of relationships. Community structure detection is a method used to identify clusters of nodes in a network. Community structure detection is the most widely studied structural features of complex networks. In this paper, we present a review about the method of community detection in hybrid network, and the application to the network analysis. Here, we present a revision of the main techniques, methods, data sets and algorithms used in the literature and, a short description of the general features of the community detection topics. Main authors and their contributions to this fields are introduced. The study is focused on the analysis of the multi-node and multi-relationship hybrid networks with the idea to apply these results to the academic network analysis. Considering the revised literature, we propose a hybrid network community detection algorithm based on meta-path, seed nodes and extend modularity method to study the academic networks.