基于转移学习和LBBA模型的节能产品在线评论的情绪分析
Jingwen Na1, Ruyin Long1, Hong Chen1
1School of Business, Jiangnan University, Wuxi, 214122, China; The Institute for National Security and Green Development, Jiangnan University, Wuxi, 214122, China.
Journal of environmental management
|May 13, 2024
概括
对节能冰箱的在线评论进行分析,揭示了消费者的关键问题. 本研究使用文本挖掘和LBBA模型来了解用户情绪,并改进绿色产品开发以实现双碳目标.
科学领域:
- 环境科学 环境科学
- 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:
- 越来越多的环境意识和气候变化推动了对绿色消费的需求.
- 节能产品对于实现二氧化碳目标至关重要.
- 现有的节能产品在有效性,噪音和成本效益方面面临挑战.
研究的目的:
- 分析用户对1级节能冰箱的在线评论.
- 使用文本挖掘提取消费特征和情绪.
- 使用LBBA模型探索消费者感兴趣的主题和情感特征.
主要方法:
- 在淘宝电子商务平台上使用了文本挖掘的评论.
- 用户隐藏的迪里克莱特分配 (LDA) 用于属性和重量识别.
- 应用Bert,BiLSTM和注意力机制进行情绪分析和预测.
- 使用转移学习来确定情绪倾向和驱动因素.
主要成果:
- 确定了消费者对节能冰箱的具体担忧.
- 提取了关键的消费特征和情绪属性.
- 揭示了消费者情绪类别背后的主要驱动因素.
结论:
- 在线评论的情绪分析提供了关于消费者对节能产品的意图的见解.
- 这些发现有助于决策者管理节能产品市场.
- 这项研究有助于提高绿色消费产品的开发和市场表现.
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