Title :
Opinion mining: A study on semantic orientation analysis for online document
Author :
Yu, Lei ; Ma, Jia ; Tsuchiya, Seiji ; Ren, Fuji
Author_Institution :
Fac. of Eng., Univ. of Tokushima, Tokushima
Abstract :
As a result of advance in technology, there now exist a large amount of online documents in the form of surveys or called reviews. Most of the previous work on text classification is focusing on sentiment text classification. Sentiment classification requires the knowledge data of vocabulariespsila semantic meaning and the relationships between the vocabularies. In this paper, sentiment features of text were divided into characteristic words and phrases, which were extracted from the training data. The method combining HowNet with sentiment classifier was proposed. It computed semantic similarity of characteristic words, phrases with tagged words in HowNet, and it adopted the positive and negative terms as features of sentiment classifier. In the test, a sentiment classifier was designed to compare with the other methods. Evaluation results show the effectiveness of our method.
Keywords :
classification; data mining; text analysis; HowNet; online document analysis; opinion mining; semantic orientation analysis; sentiment text classification; Automation; Data mining; Intelligent control; Internet; Spatial databases; Testing; Text analysis; Text categorization; Training data; Vocabulary; HowNet; Opinion Mining; Sentiment classification; Text semantic orientation;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4594529