We propose a method for using discourse relations 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 abbreviations, 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 approach is an extension of the previous work .
A method to exploit discourse relations for the detection of tweets polarity was proposed in REF .
IITB-Sentiment-Analysts: Participation in Sentiment Analysis in Twitter SemEval 2013 Task
*SEM
Computer Science