Fused sentiments from social media and its relationship with consumer demand

Abstract

Social media is an ideal platform for influencers to share their experiences and product sentiments, as consumers frequently trust the recommendations of their peers. Consumer-created reviews and ratings are the preferred source of information about product and service value, price, and product quality. Social media mining is the process of storing, analyzing, and extracting useful patterns from social media data. Mining social information helps businesses in understanding the demand of their products like cars, movies, fashion goods, electronics, and so on. In this research, we present an analytical model which quantifies and engenders the insight of fused social information, gathered from multiple data sources. Subsequently, we discuss the results obtained by the proposed model for some movie use cases like “Angry Birds” by sourcing data from Twitter, Rotten Tomatoes, and the Internet Movie Database (IMDB).