E3S Web Conf.
Volume 235, 20212020 International Conference on New Energy Technology and Industrial Development (NETID 2020)
|Number of page(s)||4|
|Section||Analysis on the Development of Intelligent Supply Chain and Internet Digital Industrialization|
|Published online||03 February 2021|
Studies on the influencing factors and prediction of product star change in the process of e-commerce transaction based on BP neural network and VAR models
College of Economics, Sichuan Agricultural University, Chengdu, China
2 College of Economics, Sichuan Agricultural University, Chengdu, China
3 College of Resources, Sichuan Agricultural University, Chengdu, China
4 College of Economics, Sichuan Agricultural University, Chengdu, China
Based on the data of reviews and scores of pacifiers sold in Amazon online market from February 2011 to August 2015, this paper extracts the text emotion words and the deviation degree of text content from the theme through the LDA theme model, and then combines the text length, based on VAR model to analyze the impact of the overall star level volatility of the market by comment length, text emotional words and topic deviation. Further, this study compare the prediction of star level by VAR model and BP neural network model, and finally put forward a more stable prediction model.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.