Sarcasm is an expression of humor, mockery or criticism with the help of ironic remarks that seems positive. Sarcasm detection in sentiment analysis is essential for understanding the emotions and thoughts of the people. Automatic sarcasm detection refers to the detection of sarcasm in the text written in natural language. Various natural language processing techniques carry out this purpose. Recognition of Sarcasm is of extraordinary significance and is valuable to numerous NLP applications such as Opinion Mining and multiple advertisings. Sarcasm detection is a complex task, because of the challenges involved in determining the nature of the sarcasm bearing text. Automatic sarcasm detection is thus, one of the hardest challenges in Sentiment Analysis, including complex linguistic analyzing and machine learning methods. This paper focuses on various sarcasm analyzing techniques employed for filtering of sarcastic statements from a text and the use of Automatic sarcasm detection in the categorization of tweets and product review texts.
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