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This project is an experiment to find if a tweet is sarcastic and Brown clustering of similar words, topics association with sarcasm - used to generate feature vectors, POS - tagging, n-gram feature vector generation, sentiment analysis of the tweets and scoring based on positivity(negativity) of the words in a tweet to find the mix of positive sentiment and negative actions are some of the techniques used to identify sarcasm. The 'kitchen sink' of a mix of these features helped us achieve close to ~58% accuracy. Languages - JAVA, Python, iPython - NLP_Sarcasm_Detection/normal_tweets.csv at master · deepakkumar-b/NLP_Sarcasm_Detection
NLP_Sarcasm_Detection/normal_tweets.csv at master · deepakkumar-b