Detection of Sarcasm from Consumer Sentiments on Social Media About Luxury Brands

Abstract

Social media sites act as a platform for customers to express their opinions/sentiments on brands and products. The opinion of the customers in social media in case of luxury brands plays a great role in improving the sales by building a better brand strategy. Most of the existing analysis used by the luxury brand industry ignores the importance of sarcasm analysis. A common type of sarcasm that is given in the form of opinion is positive sentiments, which contain a negative meaning. This paper studies the scope of Lexicon based approach, K-means and Naïve Bayes for analyzing the sarcastic opinion and analyzing the impact of these algorithms in recognition of sarcasm, which has a negative context for analyzing the luxury, brand data.