Clustering of Blog Sites Using Collective Wisdom

Abstract

The blogosphere is expanding at an unprecedented speed. A better understanding of the blogosphere can greatly facilitate the development of the social Web to serve the needs of users, service providers, and advertisers. One important task in this process is the clustering of blog sites. Although a good number of traditional clustering methods exist, they are not designed to take into account the blogosphere’s unique characteristics. Clustering blog sites presents new challenges. A prominent feature of the social Web is that many enthusiastic bloggers voluntarily write, tag, and catalog their posts in order to reach the widest possible audience who will share their thoughts and appreciate their ideas. In the process, a new kind of collective wisdom is generated. The objective of this work is to make use of this collective wisdom in the clustering of blog sites. As such, we study how clustering with collective wisdom can be achieved and compare its performance with respect to representative traditional clustering methods. Here contain, we will present statistical and visual results, report findings, opportunities for future research work, and estimated timeline, extending this work to many real-world applications.