Identifying Significance of Product Features on Customer Satisfaction Recognizing Public Sentiment Polarity: Analysis of Smart Phone Industry Using Machine-Learning Approaches

Abstract

ABSTRACT The reality about human behavior is that how other people think and evaluate have strong influences on our beliefs and thinking. Consumers get rich information from online reviews that may reduce their uncertainty regarding purchases. Besides, product-developing companies analyze user demands from online reviews to design market-driven product. In this study, a comparison among five major market share holder smart phone brands - Samsung, Apple, Huawei, Xiaomi, and Oppo is performed in different price categories - high, mid, and low range, based on sentiment polarity score. Online public reviews are extracted and sentiment scores of reviews are calculated to construct public sentiment polarity toward the famous brands. By examining both quantitative and qualitative methodologies, we identified the most important smart phone features or attributes that have great significance on consumer satisfaction. By experimenting and comparing five efficient machine-learning algorithms in predicting sentiment polarity and three feature selection algorithms in reducing attributes, an optimal set of 21 smart phone attributes was found those play major roles in determining customer satisfaction.