Please use this identifier to cite or link to this item:
|Title:||Sentix: An aspect and domain sensitive sentiment lexicon|
|Citation:||Lek, H.H., Poo, D.C.C. (2012). Sentix: An aspect and domain sensitive sentiment lexicon. Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI 1 : 261-268. ScholarBank@NUS Repository. https://doi.org/10.1109/ICTAI.2012.43|
|Abstract:||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. © 2012 IEEE.|
|Source Title:||Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Sep 20, 2018
WEB OF SCIENCETM
checked on Sep 4, 2018
checked on Aug 3, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.