Classification of Sarcastic and Non-Sarcastic Tweets Using Machine Learning

When someone is being sarcastic, they are expressing their negative emotions through the use of positive or exaggerated positive language. A person's tone of voice and body language, such as eye rolling, hand gestures, etc., might give away their sarcasm. Without these non-verbal cues, such as tone of voice and body language, a human being would have a very difficult time detecting sarcasm in written data. These difficulties explain the growing interest in sarcasm detection of social media text, particularly tweets. Major difficulties arise from analysing the ever-increasing volume of tweets. We suggested a machine learning-based framework that can collect tweets in real time and analyse them with algorithms that can accurately detect sarcastic sentiment. We find that the analysis and processing time under an ML-based framework vastly surpasses the traditional methods and is better suited for continuously streaming tweets in real time.