Blog Hotness Evaluation Model Based on Text Opinion Analysis

Author

Li, Jianjiang ; Zhang, Xuechun ; Weng, Yu ; Hu, Changjun

Author_Institution

Dept. of Comput. Sci. & Technol., Univ. of Sci. & Technol., Beijing, China

fYear

2009

fDate

12-14 Dec. 2009

Firstpage

235

Lastpage

240

Abstract

Aiming at the deficiencies of traditional blog hotness evaluation methods, the paper presents a blog hotness evaluation model based on text opinion analysis (named BHEM-TOA). The model not only considers the number of reviews, comments and publication time of the blog topic, but also focuses on the comment opinion. BHEM-TOA emphasizes subjective opinions of reviewers about the blog topic. It utilizes the text opinion analysis method based on Chinese characters to extract opinioned comments, gets supportive and oppositive circumstances about the blog topic, then combines with the number of reviews, comments and publication time to realize blog hotness evaluation. To validate the performance of BHEM-TOA, the experiment constructs two data corpuses called TOAC and BHEC, and the experimental results demonstrate that BHEM-TOA could more precisely and comprehensively evaluate the hotness of the blog than traditional methods.

Keywords

Web sites; natural language processing; text analysis; BHEM-TOA; Chinese characters; blog hotness evaluation model; data corpuses; text opinion analysis; Classification algorithms; Computer science; Data mining; Discussion forums; Information services; Internet; Labeling; Neural networks; Paper technology; Web sites; blog hotness; hot topic; text opinion analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Dependable, Autonomic and Secure Computing, 2009. DASC '09. Eighth IEEE International Conference on

Conference_Location

Chengdu

Print_ISBN

978-0-7695-3929-4

Electronic_ISBN

978-1-4244-5421-1

Type

conf

DOI

10.1109/DASC.2009.82

Filename

5380356