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E-Commerce Review Sentiment Analysis and Purchase Intention Prediction Based on Deep Learning Technology
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Author(s): Xiaoye Ma (Guilin University of Electronic Technology, China), Yanyan Li (Zhejiang Shuren University, China)and Muhammad Asif (National Textile University, Pakistan)
Copyright: 2024
Volume: 36
Issue: 1
Pages: 29
Source title:
Journal of Organizational and End User Computing (JOEUC)
Editor(s)-in-Chief: Sangbing (Jason) Tsai (International Engineering and Technology Institute (IETI), Hong Kong)and Wei Liu (Qingdao University, China)
DOI: 10.4018/JOEUC.335122
Purchase
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Abstract
This study proposes a deep learning-based analytical model to conduct an in-depth study of the relationship between consumer trust, perceived benefits, and purchase intention. This model combines natural language processing and sentiment analysis, using the BERT-LSTNet-Softmax model to extract textual features in reviews and perform temporal predictions of consumer sentiment and purchase intention. Experimental results show that this model achieves excellent performance in the e-commerce field and provides a powerful tool for in-depth understanding of consumer purchasing decisions. This research promotes the application of deep learning technology in the field of e-commerce, helps to improve the accuracy of consumer purchase intentions, and provides more support for the development of the e-commerce market and consumer decision-making.
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