DocumentCode :
2628627
Title :
SentiFul: Generating a reliable lexicon for sentiment analysis
Author :
Neviarouskaya, Alena ; Prendinger, Helmut ; Ishizuka, Mitsuru
Author_Institution :
Univ. of Tokyo, Tokyo, Japan
fYear :
2009
fDate :
10-12 Sept. 2009
Firstpage :
1
Lastpage :
6
Abstract :
The main drawback of any lexicon-based sentiment analysis system is the lack of scalability. Thus, in this paper, we will describe methods to automatically generate and score a new sentiment lexicon, called SentiFul, and expand it through direct synonymy relations and morphologic modifications with known lexical units. We propose to distinguish four types of affixes (used to derive new words) depending on the role they play with regard to sentiment features: propagating, reversing, intensifying, and weakening.
Keywords :
emotion recognition; natural language processing; psychology; SentiFul; morphologic modification; sentiment features; sentiment lexicon; synonymy relations; Clustering algorithms; Data mining; Informatics; Machine learning; Machine learning algorithms; Mutual information; Scalability; Spatial databases; Tagging; Target recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Affective Computing and Intelligent Interaction and Workshops, 2009. ACII 2009. 3rd International Conference on
Conference_Location :
Amsterdam
Print_ISBN :
978-1-4244-4800-5
Electronic_ISBN :
978-1-4244-4799-2
Type :
conf
DOI :
10.1109/ACII.2009.5349575
Filename :
5349575
Link To Document :
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