A dynamic adjustment algorithm research of sentiment word weight based on context

Author

Xu Ye-qiang ; Zhu Yan-hui ; Wen-hua, Wang ; Gao Li-chun

Author_Institution

Inst. of Comput. & Commun., Hunan Univ. of Technol., Zhuzhou, China

Volume

3

fYear

2011

fDate

11-13 March 2011

Firstpage

19

Lastpage

22

Abstract

The emotion tendency of sentiment word is divided into two types: static emotion tendency and dynamic emotion tendency. Basic semantic lexicon is static emotion tendency, in the real context, but it is different between static emotion tendency and dynamic emotion tendency. The paper proposes a method based on degree lexicon, negative lexicon and dependence relationship of sentence elements. The experimental results show dynamic emotion tendency even more reflects text emotion tendency and get best performance in text sentiment classification.

Keywords

text analysis; dynamic adjustment algorithm research; dynamic emotion tendency; sentiment word weight; static emotion tendency; text emotion tendency; text sentiment classification; Buildings; Computers; Context; Data mining; Feature extraction; Heuristic algorithms; Semantics; dynamic adjustment algorithm of sentiment word weight; dynamic emotion tendency; sentiment classification; static emotion tendency;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Research and Development (ICCRD), 2011 3rd International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-61284-839-6

Type

conf

DOI

10.1109/ICCRD.2011.5764236

Filename

5764236