Community detection: Topological vs. topical

Systematic analysis of applying a topology-based community detection approach and a topic-basedcommunity detection approach to the coauthorship networks of the information retrieval area found that communities detected by the topological approach tend to contain different topics within each community.

Abstract

The evolution of the Web has promoted a growing interest in social network analysis, such as community detection. Among many different community detection approaches, there are two kinds that we want to address: one considers the graph structure of the network (topology-based community detection approach); the other one takes the textual information of the network nodes into consideration (topic-based community detection approach). This paper conducted systematic analysis of applying a topology-based community detection approach and a topic-based community detection approach to the coauthorship networks of the information retrieval area and found that: (1) communities detected by the topology-based community detection approach tend to contain different topics within each community; and (2) communities detected by the topic-based community detection approach tend to contain topologically-diverse sub-communities within each community. The future community detection approaches should not only emphasize the relationship between communities and topics, but also consider the dynamic changes of communities and topics.