Who cares about Sarcastic Tweets? Investigating the Impact of Sarcasm on Sentiment Analysis.

Abstract

Sarcasm is a common phenomenon in social media, and is inherently difficult to analyse, not just automatically but often for humans
\ntoo. It has an important effect on sentiment, but is usually ignored in social media analysis, because it is considered too tricky to handle.
\nWhile there exist a few systems which can detect sarcasm, almost no work has been carried out on studying the effect that sarcasm has on
\nsentiment in tweets, and on incorporating this into automatic tools for sentiment analysis. We perform an analysis of the effect of sarcasm
\nscope on the polarity of tweets, and have compiled a number of rules which enable us to improve the accuracy of sentiment analysis when
\nsarcasm is known to be present. We consider in particular the effect of sentiment and sarcasm contained in hashtags, and have developed
\na hashtag tokeniser for GATE, so that sentiment and sarcasm found within hashtags can be detected more easily. According to our experiments,
\nthe hashtag tokenisation achieves 98% Precision, while the sarcasm detection achieved 91% Precision and polarity detection 80%.