Paper: IITB-Sentiment-Analysts: Participation in Sentiment Analysis in Twitter SemEval 2013 Task

ACL ID S13-2082
Title IITB-Sentiment-Analysts: Participation in Sentiment Analysis in Twitter SemEval 2013 Task
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

We propose a method for using discourse rela- tions for polarity detection of tweets. We have focused on unstructured and noisy text like tweets on which linguistic tools like parsers and POS-taggers don?t work properly. We have showed how conjunctions, connectives, modals and conditionals affect the sentiments in tweets. We have also handled the commonly used ab- breviations, slangs and collocations which are usually used in short text messages like tweets. This work focuses on a Web based application which produces results in real time. This ap- proach is an extension of the previous work (Mukherjee et al. 2012).