As the cross-border mobile e-commerce food market is rapidly booming, food safety issues are becoming more and more prominent. To effectively respond to this challenge, this study applies the BTM (Biterm Topic Model) thematic model to deeply analyze the food safety user reviews on cross-border mobile e-commerce platforms. We first selected and collected platform data that met the research requirements and performed the necessary preprocessing. Subsequently, the review texts were analyzed using the BTM model, including topic intensity distribution, word cloud mapping, word frequency weight visualization, and quantitative output of word item relevance. Through these analyses, we delved into the manifestation of food safety issues in three aspects: topic intensity, topic domain, and subject structure, identified five specific types of food safety issues, and revealed the reasons behind them. The findings suggest that AMAZON US cross-border mobile e-commerce platform has some problems with food safety regulations. In response to these findings, we propose a series of targeted recommendations for improvement, which are relevant to other cross-border e-commerce platforms. These discoveries will offer valuable insights for the operation and oversight of cross-border mobile e-commerce platforms, fostering the sustainable growth of the cross-border food trade, safeguarding consumer rights and interests, mitigating platform risks, and ultimately promoting the long-term expansion of the industry.
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Title
Analysis of Food Safety Issues in Cross-Border Mobile E-commerce Platforms Based on BTM-Taking Amazon US User Reviews as an Example
Publication Details
Human-Centered Design, Operation and Evaluation of Mobile Communications, Vol.14738, pp.119-132