Title :
Extracting the Opinions of News Articles based on Emotionally Laden Words
Author :
Shinomiya, Mizuho ; Ren, Fuji ; Kuroiwa, Shingo ; Tsuchiya, Seiji
Author_Institution :
Grad. Sch. of Adv. Technol. & Sci., Tokushima Univ., Tokushima
fDate :
Aug. 30 2007-Sept. 1 2007
Abstract :
In this paper we propose an approach to extract the opinion of the media from news articles based on emotionally laden words. In the propose approach, the opinions are judged by the total number of the emotion levels from articles. The emotion level is the number from -3 to +3 that indicate emotionally laden words whether have plus or minus images. The articles of baseball game and the editorial article are used as experiment object. The precision of the propose approach on the articles about baseball game is 66%, and on the articles of political event is 36%.
Keywords :
information retrieval; baseball game; emotionally laden words; news articles; opinions extraction; political event; Blogs; Data mining; Frequency; Internet; Paper technology;
Conference_Titel :
Natural Language Processing and Knowledge Engineering, 2007. NLP-KE 2007. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1610-3
Electronic_ISBN :
978-1-4244-1611-0
DOI :
10.1109/NLPKE.2007.4368041
