User sentiment analysis based on social network information and its application in consumer reconstruction intention

Abstract Due to the increasingly fierce competition in the consumer goods market, customer retention strategies are of great importance for enterprises to maintain their dominance and long-term and stable earnings. Understanding customer repurchase intention and re-patronage is the prerequisite and foundation for business and retailers. Online reviews include ratings and emotional information from many customers on brands and online stores. Consumer repurchase intention can be measured by mining the attitudes and emotions of consumers in the reviews. Based on online reviews, this work used textual sentiment calculation and fuzzy mathematics to study the online repurchase intention of online consumers. Taking satisfaction, trust and promotion efforts as the antecedents, and consumer repurchase intention as the consequent, a model was established based on emotional computing and fuzzy reasoning. Through the satisfaction, trust and promotion effort of five sportswear brands in Taobao, we verified the reasoning for determining consumer repurchase intention of products. Meanwhile, the relationship between the initial purchase intention and repurchase intention of consumers was compared, thus providing the basis for online stores to formulate their marketing strategy and brand segmentation.