Sentix: An Aspect and Domain Sensitive Sentiment Lexicon

Sentiment lexicons have often been used to aid sentiment analysis. Most of these sentiment lexicons are general-purpose lexicons which assign a fixed polarity to every word. However, it has been noted that the polarity of words depends on both the aspect and domain, thus a general-purpose sentiment...

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Bibliographic Details
Published in2012 IEEE 24th International Conference on Tools with Artificial Intelligence Vol. 1; pp. 261 - 268
Main Authors Hsiang Hui Lek, Poo, D. C. C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2012
Subjects
Aspect Ranking
Batteries
Cameras
Digital audio players
Feature extraction
Filtering
Lexicon Induction
Mobile handsets
Opinion Mining
Sentiment analysis
Sentiment Lexicon
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Summary:Sentiment lexicons have often been used to aid sentiment analysis. Most of these sentiment lexicons are general-purpose lexicons which assign a fixed polarity to every word. However, it has been noted that the polarity of words depends on both the aspect and domain, thus a general-purpose sentiment lexicon would not be able to accurately classify the sentiment of words. This paper proposes a method to automatically construct an aspect and domain sensitive sentiment lexicon which assigns polarity to a word depending on its aspect and domain, and make available Sentix which is an aspect and domain sensitive sentiment lexicon spanning over 200 product domains. Experimental results have shown that our lexicon produces significantly better results compared to other commonly used lexicons. We also observe the long tail distribution behavior of product aspects, and propose the possibility of aspect ranking by comparing the number of domains and number of sentiment words present for an aspect.
ISBN:1479902276
9781479902279
ISSN:1082-3409
2375-0197
DOI:10.1109/ICTAI.2012.43