A clustering method of bloggers based on social annotations. (27th January 2011)

• Record Type: Journal Article
• Authors: Sakurai, Shigeaki; Tsutsui, Hideki
• Is Part Of: International journal of business intelligence and data mining. Volume 6:Number 1(2011)
• Page Start: 26
• Page End: 41
• Publication Date: 2011-01-27
• Subjects: social annotations -- k-means method -- similarity coefficient -- bloggers -- communication support sites -- blogs -- weblogs -- blogger clusters -- clustering; 006.312
• Languages: English
• ISSNs: 1743-8187

Abstract

This paper proposes a method that divides bloggers to clusters according to their interests. The method calculates similarities between the bloggers based on three steps. That is, the method calculates similarities between target objects discussed in blog articles based on social annotations. It calculates similarities between impressions related to the target objects based on impression words included in blog articles. Here, products, works and services are examples of the target objects. Lastly, the method calculates similarities between the bloggers by combining the results of the method's first and second calculation steps, and divides the bloggers to clusters based on the similarities. The paper applies the method to the Commutents data and the Yahoo! Japan Movie data, and verifies the effectiveness of the method.