基于多功能融合的消费者感知风险预测及其解释性研究
Lin Qi1,2, Yunjie Xie1,3, Qianqian Zhang1,3
1School of Economics & Management, Beijing Information Science & Technology University, Beijing, China.
PloS one
|January 3, 2025
概括
这项研究使用审查内容和网站数据预测电子商务的感知风险. 质量,安全和价格等关键特征显著影响用户的风险感知.
科学领域:
- 电子商务是一个电子商务.
- 消费者行为 消费者行为
- 数据科学数据科学数据科学
背景情况:
- 电子商务面临着诸如内容均化和高用户感知风险等挑战.
- 分析在线评论和网站数据对于理解和减轻这些风险至关重要.
研究的目的:
- 开发电子商务中感知风险的预测模型.
- 确定影响不同产品类别感知风险的关键特征.
主要方法:
- 使用KeyBERT-TextCNN从262,752个在线评论中提取主题功能.
- 结合主题特征与产品/商户数据.
- 使用PCA-K-medoids-XGBoost进行预测建模.
主要成果:
- 确定了影响感知风险的11个关键特征.
- 实现了高性能,精度为84%,回忆率为86%,F1得分为85%.
- 质量,功能和价格对于电子产品至关重要;皮肤安全对于护肤至关重要.
结论:
- 开发的模型有效预测了电子商务中感知到的风险.
- 功能的重要性因产品类型而异,突出显示了需要特定上下文分析的需要.
- 高风险样本和正常样本之间存在显著差异,为风险缓解策略提供了信息.
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