Title :
SentiFul: Generating a reliable lexicon for sentiment analysis
Author :
Neviarouskaya, Alena ; Prendinger, Helmut ; Ishizuka, Mitsuru
Author_Institution :
Univ. of Tokyo, Tokyo, Japan
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;
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
DOI :
10.1109/ACII.2009.5349575