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使用社交媒体评论开发食品安全信号的因果关系和严重性评估框架:基于城市印度郊区数据的技术报告
Akash Prabhune1,2, Vinay Sri Hari2, Neeraj Kumar Sethiya1
1Faculty of Pharmacy, School of Pharmaceutical and Populations Health Informatics (SoPPHI), DIT University, Dehradun, IND.
Cureus
|August 12, 2024
概括
一个使用社交媒体评论和人工智能的新框架分析了印度餐厅的食品安全. 它在40%的机构中发现了重大问题,使公共卫生优先进行纠正行动.
科学领域:
- 公共卫生 公共卫生
- 计算机科学 计算机科学
- 食品科学 食品科学 食品科学
背景情况:
- 社交媒体评论为消费者体验和商业互动提供了洞察力.
- 有效的食品安全监督对城市公共卫生至关重要.
研究的目的:
- 通过使用社交媒体数据,开发印度城市食品安全的被动监控框架.
- 识别和评估在线餐厅评论中的食品安全信号.
主要方法:
- 使用一个双向编码器表示从变压器 (BERT) 驱动的面向基于情感分析工具 (吃在正确的地方 - ERP).
- 分析了来自93家餐厅的超过10万条评论.
- 引入因果关系评估指数 (CAI) 和严重性评估分数 (SAS) 用于风险评估.
主要成果:
- 在40%的餐馆中发现了严重的食品安全问题,CAI值高于1.
- 该框架成功地对食品安全问题的严重性进行了分级.
- 实时食品安全管理和纠正行动的优先级的潜力.
结论:
- 整合基于数据的方法,如人工智能和社交媒体分析,可以增强公共卫生监测系统.
- 开发的框架支持及时进行监管干预,以改善食品安全.
- 未来的工作应该集中在完善自然语言处理算法和扩大数据源.
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