Mining shared social media links to support clustering of blog articles

Abstract

When monitoring blog articles for the tracking of a certain personality or product, the automatic identification of topic clusters is of high interest. Clustering by textual content is a popular method to accomplish this. In this paper we investigate how links between individual blog articles can be used to support this clustering with another dimension of information. Given the existing component structure of these networks, we focus on the extension with links based on shared social media resources. We show that the component structure extended in this way is of very high use for supporting textual clustering algorithms, and may be used for a new type of hybrid clustering algorithms in the future.