The sentiment is an attitude or opinion that is expressed, it is not based on laws and philosophy. Sentiment analysis is the mining of opinion or sentiment expressed in text as positive, negative or neutral sentiment. Detecting sarcasm is the main hurdle in sentiment analysis. Sarcasm can be expressed in various forms like in conversation, heading or title of the novel. As Sarcasm represents contrary sentiment to the literal meaning that is conveyed in the text, it is hard to identify sarcasm even for a human. This paper presents a study on sentiment analysis. The datasets, feature engineering, and algorithm used in previous models for sarcasm detection. The study proves that Support vector machine (SVM) is the finest approach for sarcasm detection, feature engineering is an import assent in training a model and as News Headline dataset is written by professionals, it is the most suitable data set to work on.
Categories: Data
