A clustering method of bloggers based on social annotations Online publication date: Wed, 22-Apr-2015
by Shigeaki Sakurai, Hideki Tsutsui
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 6, No. 1, 2011
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Intelligence and Data Mining (IJBIDM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com