Clustering of tag-induced sub-graphs in complex networks

TL;DR

This paper investigates how the clustering coefficient in tagged networks varies when focusing on sub-graphs defined by specific tags, revealing insights into the network's structure and node properties.

Contribution

It introduces an analysis of clustering coefficient behavior in tag-induced sub-graphs and explores its correlation with other network properties, enhancing understanding of complex systems.

Findings

Clustering coefficient varies significantly across tag-induced sub-graphs.

Node clustering coefficients are influenced by node tags.

The analysis provides a more complete structural description of large networks.

Abstract

We study the behavior of the clustering coefficient in tagged networks. The rich variety of tags associated with the nodes in the studied systems provide additional information about the entities represented by the nodes which can be important for practical applications like searching in the networks. Here we examine how the clustering coefficient changes when narrowing the network to a sub-graph marked by a given tag, and how does it correlate with various other properties of the sub-graph. Another interesting question addressed in the paper is how the clustering coefficient of the individual nodes is affected by the tags on the node. We believe these sort of analysis help acquiring a more complete description of the structure of large complex systems.