An Emoticon Based Sarcastic Sentiment Analysis on Live Streaming Data of Twitter

Sentiment Analysis (SA) is a methodology in the data mining field. It plays a crucial role in the opinion mining, statistical experiments especially in the field of text mining. Generally an analysis can be made depending on the requirement given for the user. Coming to the social media, it is becoming a vast space for the people to share their views and ideas. Intentionally they make comments like reviewing a particular topic regarding its positive and negative thoughts. This can be made by Sentiment Analysis which is used in determining the opinions of the commentators. In this paper, an analysis is done on the sarcastic opinions or reviews based on the] emoticons and short texts, which are now very familiar in posted in a social media like Twitter. Twitter will be having many tweets regarding various cases like movies, restaurants, particular person, etc. A text in the review may not give the full result regarding an opinion. So, emoticon can give maximum accuracy in determining the sarcastic opinions of the users. The main intention of the paper is to analyze the tweets called as reviews of the specific topic dynamically and calculating the review rate using the combination of short texts and emojis.