A Study on Identification of Opinion Holders and Analysis of Their Viewpoints
Date Issued
2009
Date
2009
Author(s)
Lee, Chia-Ying
Abstract
People write various articles in order to express their opinions. The opinion includes opinion polarity, opinion strength, opinion target and opinion holder. In this paper, we focus on the identification of opinion holders. In each article, the opinion holder could be the post-author or a nominal (noun, noun phrase or named entity) which issues some opinions in the article. In this paper, the task of opinion holder identification is divided into two subtasks: identification of author’s opinions and labeling of opinion holders, respectively. In this paper, we apply SVM (Support Vector Machine) and CRF (Conditional random field) to automatically extract opinion holders. The SVM is adopted to identify author’s opinions, and the CRF is utilized to label opinion holders (i.e., nominals). We propose some features including lexical features, part-of-speech features, named entity features, punctuation mark features, position features, context features and opinion-word features in the SVM and the CRF. Finally, the mining process will combine the result of the SVM and CRF. In experiments, the proposed method achieves the F-score 0.734 in NTCIR7 MOAT task at traditional Chinese side. It is best than other teams who utility learning methods.
Subjects
opinion holder identification
opinion viewpoint analysis
opinion mining
conditional random field
CRF
support vector machine
SVM
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-98-R96922084-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):dec5b7c61c9cf9bb4084438fd48c2ffe