Sentiment analysis based on the domain dictionary: a case of analysing online apparel reviews

Abstract

E-commerce offers an online shopping environment in which manufacturers, businesses, and consumers participate. The past-customer emotion outlined in their reviews plays an important role in not only the purchasing decisions of potential consumers, but also in manufacturers' production plans and in business' maintenance of their shopping environments. This paper proposes a sentiment analysis approach based on the domain dictionary for extracting subjective customer emotion and objective commodity metadata from review pages and analysing their relationships. The value of the proposed approach was demonstrated through a case study by using online apparel reviews of an anonymous brand in China. The study found that the domain dictionary can be more effective in extracting emotional information. Coats, shirts, and t-shirts garner higher emotions than pants. Sales increase as the emotion increases and decrease as the price increases. A fixed price range, in which the clothing has higher emotion and sales, can be found.