Creating a Chinese emotion lexicon based on corpus Ren-CECps

Author

Li, Ji ; Ren, Fuji

Author_Institution

Dept. of Inf. Sci. & Intell. Syst., Univ. of Tokushima, Tokushima, Japan

fYear

2011

fDate

15-17 Sept. 2011

Firstpage

80

Lastpage

84

Abstract

As a basic emotion resource, an emotion lexicon plays a very important role in the classification and recognition of emotion in text. This paper proposes an automatic approach to create a Chinese emotion lexicon with tag of emotion intensity based on the emotion corpus Ren-CECps 1.0. We present a new algorithm of emotion vector computation by making use of two language dictionaries Tongyici Cilin and HowNet. Comparing with the experimental results on verbs by SVM classification method, our approach is proved feasible and effective.

Keywords

emotion recognition; pattern classification; support vector machines; text analysis; Chinese emotion lexicon; HowNet language dictionary; Ren-CECps emotion corpus; SVM classification method; Tongyici Cilin language dictionary; emotion classification; emotion intensity tag; emotion recognition; emotion text; support vector machines; Classification algorithms; Dictionaries; Emotion recognition; Noise; Semantics; Support vector machine classification; Emotion Intensity; Emotion Lexicon; HowNet; SVM; Semantic Similarity; Tongyici Cilin;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Computing and Intelligence Systems (CCIS), 2011 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-61284-203-5

Type

conf

DOI

10.1109/CCIS.2011.6045036

Filename

6045036