A classification method for social information of sellers on social network

Abstract

Abstract Social e-commerce has been a hot topic in recent years, with the number of users increasing year by year and the transaction money exploding. Unlike traditional e-commerce, the main activities of social e-commerce are on social network apps. To classify sellers by the merchandise, this article designs and implements a social network seller classification scheme. We develop an app, which runs on the mobile phones of the sellers and provides the operating environment and automated assistance capabilities of social network applications. The app can collect social information published by the sellers during the assistance process, uploads to the server to perform model training on the data. We collect 38,970 sellers’ information, extract the text information in the picture with the help of OCR, and establish a deep learning model based on BERT to classify the merchandise of sellers. In the final experiment, we achieve an accuracy of more than 90%, which shows that the model can accurately classify sellers on a social network.

Keywords

• User model
• Machine learning
• Social e-commerce