Comparative Analysis of Different NLP Techniq...

Comparative Analysis of Different NLP Techniques for Detecting Sarcasm on Twitter

Author Name : Priyanka Bolinjkar, R.R. Sedamkar

ABSTRACT Sarcasm is a nuanced form of communication where the individual states opposite of what is implied. One of the major challenges of sarcasm detection is its ambiguous nature. There is no prescribed definition of sarcasm. Another major challenge is the growing size of the languages. Every day hundreds of new slang words are being created and used on these sites. Hence, the existing corpus of positive and negative sentiments may not prove to be accurate in detecting sarcasm. Due to these difficulties and the inherently tricky nature of sarcasm it is generally ignored during social network analysis. As a result the results of such analysis are affected adversely. Detection of sarcastic content is vital to various NLP based systems such as text summarization and sentiment analysis. Sarcasm might be used for different purposes, such as criticism or mockery. However, it is hard even for humans to recognize. Therefore, recognizing sarcastic statements can be very useful to improve automatic sentiment analysis of data collected from micro blogging websites or social networks. Sentiment Analysis refers to the identification and aggregation of attitudes and opinions expressed by Internet users toward a specific topic.