Visualizing community centric network layouts

We present our COMmunity Boundary (COMB) and COMmunity Circles (COMC) network layout algorithms that focus on revealing the structure of discovered communities and the relationships between these communities. We believe this information is vital when developing new community mining algorithms as it...

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Bibliographic Details
Main Authors: Fagnan, J., Zaiane, O., Goebel, R.
Format: Conference Proceeding
Language:English
Subjects:
Communities
Feeds
Force
Inference algorithms
Layout
Proteins
Visualization
Online Access:Request full text
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Description
Summary:We present our COMmunity Boundary (COMB) and COMmunity Circles (COMC) network layout algorithms that focus on revealing the structure of discovered communities and the relationships between these communities. We believe this information is vital when developing new community mining algorithms as it allows the viewer to more quickly assess the quality of a mining result without appealing to large tables of statistics. To implement our algorithms we have introduced numerous modifications to the existing Fruchterman-Reingold layout, including support for multi-sized vertices, removal of the bounding frame, introduction of circular bounding boxes, and a novel slotting system. Our evaluation argues that both COMB and COMC outperform existing alternatives in their ability to reveal community structure and emphasize inter-community relations.
ISSN:1550-6037
2375-0138
DOI:10.1109/IV.2012.61