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

  • V. HaripriyaEmail author
  • Poornima G. PatilEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1037)

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.

Keywords

Machine learning Sarcasm Branding strategy K-means Naïve Bayes Lexicon based 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of MCAJain Deemed-to-be UniversityBangaloreIndia
  2. 2.Department of MCAVisvesvaraya Technological UniversityBelagaviIndia

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