Understanding sarcasm from reddit texts using supervised algorithms

Abstract

The use of satirical or ironic language for conveying a message is referred to as Sarcasm. Social networks such as Reddit, Twitter, etc. usually uses Sarcasm. Reddit which is an American website contains social aggregations of news, ratings of the content and discussions. These resources, which include links, text articles, photographs, and videos, are published to the platform by registered users and can be voted up or down. Posts that cover topics related to books, cooking, pets, news, politics, movies, religions, science, sports, fitness, video games, music, and image-sharing are organized as 'communities' or 'subreddits'. The submissions receiving enough outvotes appear on the front page of the site and towards the top of the subreddit. This paper is about classifying a Reddit comment as sarcastic or non-sarcastic with the help of machine learning techniques. The dataset used in this study named as 'Sarcasm on Reddit' for classi-fication according to genre-based and have followed some basic steps using supervised machine learning and deep learning algorithms for the classification of texts including pre-processing, feature extraction and modeling. In this approach, we have achieved 71%, 76% and 70% accuracy for LSTM, CNN, and Logistic Regression algorithms respectively.