Research Article
CoViFlowPro: A Community Visualization method based on a Flow Propagation Algorithm
@INPROCEEDINGS{10.4108/icst.bict.2014.257867, author={Paraskevi Fragopoulou and Costas Panagiotakis and Harris Papadakis}, title={CoViFlowPro: A Community Visualization method based on a Flow Propagation Algorithm}, proceedings={8th International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)}, publisher={ICST}, proceedings_a={BICT}, year={2015}, month={2}, keywords={community visualization complex networks community detection belief propagation}, doi={10.4108/icst.bict.2014.257867} }- Paraskevi Fragopoulou
Costas Panagiotakis
Harris Papadakis
Year: 2015
CoViFlowPro: A Community Visualization method based on a Flow Propagation Algorithm
BICT
ACM
DOI: 10.4108/icst.bict.2014.257867
Abstract
In this paper, we propose a method (CoViFlowPro) for the visualization of a community of a node based on the results of a flow propagation algorithm (FlowPro) [15]. FlowPro computes the community of a node in a network without the knowledge of the structure of the entire graph resulting at the same time to a metric that is related with the prob- ability of a node belonging to the requested community. In this work, we use this metric to visualize the community of a node on the curve of the Archimedean spiral. The novelty of CoViFlowPro is the fact that the proposed community visualization method is local and it does not require the knowledge of the entire graph as most of the existing visual- ization methods from the literature. Moreover, it visualizes the community of a node taking into account the significance of the node membership.