Research on Car Sales Prediction Based on Online Reviews and Internet Search

doi:10.12068/j.issn.1005-3026.2023.05.019

Abstract

Abstract: The emotion analysis algorithm is used to obtain the valence of online reviews， and the prospect theory and entropy method are used to adjust the valence of online reviews. Combined with the volume of reviews and Internet search data， an autoregressive distributed lag model is established to predict and analyze the sales volume of cars in different price levels. It is shown that the prediction effect of the model， which takes into account the valence， volume of online reviews and Internet search data affected by negative information， is better than that of the traditional model and more consistent with actual situations. However， there are differences in the prediction effect for cars of different price levels. The sales prediction of low-end cars is the best， followed by mid-range cars， and finally high-end cars.

Key words: online reviews; sentiment analysis; Internet search; sales forecasting; autoregressive distribution lag model

CLC Number:

F272.1

WANG Shu-tian， LIN Yan， ZHU Guo-qing， YAN Ye-jin. Research on Car Sales Prediction Based on Online Reviews and Internet Search[J]. Journal of Northeastern University(Natural Science), 2023, 44(5): 752-760.

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