Community detection: Topological vs. topical

作者:

Highlights:

摘要

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.

论文关键词:Community detection,Topics,Communities,Coauthor network

论文评审过程:Received 29 December 2010, Revised 24 February 2011, Accepted 28 February 2011, Available online 23 May 2011.

论文官网地址:https://doi.org/10.1016/j.joi.2011.02.006