Research on the Impact Factors of Consumer' Purchasing Intention Based on Online Reviews: A Big Data Architecture

Under the background of the volume of online stores with original brand increasing, the influencing factors of online consumers' purchase intention have been paid more and more attention. This paper collected online reviews for empirical analysis by constructing a big data mining framework based on chameleon clustering algorithm, and obtained hotspots about online reviews. Analytic hierarchy process is used to calculate the weights of factor. The results show that online reviews hotspots have several different degrees of impact on consumers' purchase intention. Among them, product style and material quality have the greatest impact on consumers' purchase intention, while logistics and customer service attitude, as health factors to stimulate consumers' purchase, although they can only maintain existing customers, they cannot increase the sales of product significantly.