Measuring Quadrangle Formation in Complex Networks
- Publisher:
- Institute of Electrical and Electronics Engineers (IEEE)
- Publication Type:
- Journal Article
- Citation:
- IEEE Transactions on Network Science and Engineering, 2021, PP, (99), pp. 1-1
- Issue Date:
- 2021-01-01
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The classic clustering coefficient and the lately proposed closure coefficient quantifies the formation of triangles from two different perspectives, with the focal node at the centre or at the end in an open triad. As many networks are naturally rich in triangles, they become standard metrics to describe and analyse networks. However, their utilities could be limited in many other types of networks, where triangles are relatively few and quadrangles are overrepresented, such as the protein-protein interaction networks, the neural networks and the food webs. Here we propose two quadrangle coefficients, i.e., the i-quad coefficient and the o-quad coefficient, to quantify quadrangle formation in networks, and we further extend them to weighted networks. Through experiments on 16 networks from six different domains, we first reveal the density distribution of the two quadrangle coefficients, and then analyse their correlations with node degree. Finally, we demonstrate that at network-level, adding the average i-quad coefficient and the average o-quad coefficient leads to significant improvement in network classification, while at node-level, the i-quad and o-quad coefficients are useful features to improve link prediction.
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