Social Media Platforms: Investigate Sentiment Analysis For Transforming Business Decisions In Car Segments
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Abstract
The automotive industry is one of the most significant global economic drivers. There has been a steady rise in both the expectations and the level of competition. Thus, to attain a better competitive advantage in the market, the companies carefully analyze the consumers’ opinions on social media platforms to enhance business decisions. Existing studies have shown various analyses of consumer opinion towards brands or products, particularly on one social media platform. Yet, limited studies have explored sentiment analysis in social media text and reviews of preferences of car brands. This research aims to investigate the impact of social media sentiment analysis on business choices involving automotive companies. In this study, a dataset has been taken from a total of five car brand models of Kia, Hyundai, Toyota, Maruti Suzuki, and Mahindra with three social media platforms, namely Twitter, Facebook, and Instagram. Sentiment analysis has been applied to explore the user’s opinions and reviews about five brand car models. By the utilization of Natural Language Processing (NLP), sentiment analysis evaluates the emotional polarity status of users. It showed that the brand Hyundai has achieved a much higher positive polarity sentiment score than the other model. Further, it showed that it achieved a strong correlation between business decisions and sentiment in the social media platform of Facebook, where all the brand models attained strong correlations.
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