Consumer Online Review Content Mining and Emotion Analysis Under the Background of Live Streaming E-Commerce

Fang Zhang () and Fengxiao Li ()
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Fang Zhang: Liaoning Technology University, School of Marketing Management
Fengxiao Li: Liaoning Technology University, School of Marketing Management

A chapter in Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024), 2024, pp 337-346 from Springer

Abstract: Abstract Online reviews of products in the mode of live e-commerce contain important factors that affect consumers’ purchasing decisions. The content of agricultural product reviews on the Tiktok platform was collected by Python web crawler, and 23557 agricultural product reviews were analyzed by word frequency analysis, network co-occurrence of high-frequency word meanings, LDA theme model, SnowNLP sentiment analysis and other methods. The study found that product quality, express packaging, anchor recommendation and logistics speed are the key factors affecting consumers’ online purchase decisions under the live streaming e-commerce model. On this basis, strengthening product quality, improving express packaging, improving the professionalism of anchors, and ensuring logistics speed are important measures to improve consumers’ desire to buy, and are of great significance to promote the sustainable development of the agricultural live e-commerce industry.

Keywords: electricity supplier logistics; LDA topic model; live-streaming e-commerce; agricultural products; SnowNLP sentiment analysis (search for similar items in EconPapers)
Date: 2024
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DOI: 10.2991/978-94-6463-570-6_35

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