Title: A clustering method of bloggers based on social annotations

Authors: Shigeaki Sakurai, Hideki Tsutsui

Addresses: Corporate Research and Development Center, Toshiba Corporation, 1, Komukai-Toshiba-cho, Saiwai-ku, Kawasaki 212-8582, Japan. ' NewsWatch Incorporated, 1-6-7, Shibakoen, Minato-ku, Tokyo 105-0011, Japan

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.

Keywords: social annotations; k-means method; similarity coefficient; bloggers; communication support sites; blogs; weblogs; blogger clusters; clustering.

DOI: 10.1504/IJBIDM.2011.038272

International Journal of Business Intelligence and Data Mining, 2011 Vol.6 No.1, pp.26 - 41

Available online: 26 Jan 2011 *

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