A research framework for passive surveillance for food safety from social media: Identification and evaluation of customer reviews for regulatory use and case study of 30 restaurants

A. Prabhune, N. Sethiya, Heemanshu Arora
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Abstract

The primary objective of this paper is to develop a framework for continuous monitoring of the safety of food business operators without overburdening established regulatory systems through social media for food safety. A phase-wise methodology was adopted, wherein Phase 1 was dedicated to identifying available literature on Adverse Drugs Reactions (ADR) reporting using Social Media data. Phase 2 used the data from google maps review of the restaurants to replicate a similar methodology for Food Safety Surveillance. We identified 5 themes for a complete Surveillance framework, theme 1 involves data collection from social media, theme 2 involves pre-processing of data for analysis, theme 3 involves data annotations, theme 4 involves Identifying the relationship between regulatory violation and event, and theme 5 involves evaluation of the model. We were able to demonstrate the ADR reporting methodology could be adopted till theme 3, whereas theme 4 requires the development of an algorithm to assess the causality of an event with the Food Safety Code. According to our research, it is possible to develop a passive surveillance system for food safety that adheres to the principle of ADR reporting; however, the main obstacle is the absence of a causality assessment algorithm that can link an event to the food safety code and help regulators take immediate action.
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基于社交媒体的食品安全被动监测研究框架:用于监管用途的顾客评论识别和评估,以及30家餐馆的案例研究
本文的主要目标是制定一个框架,以持续监测食品企业经营者的安全,而不会通过社会媒体对食品安全造成既定监管系统的过重负担。采用分阶段方法,其中第一阶段致力于利用社交媒体数据识别有关药物不良反应(ADR)报告的可用文献。第二阶段使用谷歌地图对餐馆进行审查的数据来复制食品安全监测的类似方法。我们为完整的监测框架确定了5个主题,主题1涉及从社交媒体收集数据,主题2涉及数据预处理以供分析,主题3涉及数据注释,主题4涉及识别监管违规与事件之间的关系,主题5涉及对模型的评估。我们能够证明ADR报告方法可以采用到主题3,而主题4需要开发一种算法来评估事件与《食品安全法》的因果关系。根据我们的研究,有可能建立一个坚持不良反应报告原则的食品安全被动监测系统;然而,主要障碍是缺乏一种因果关系评估算法,这种算法可以将事件与食品安全法规联系起来,帮助监管机构立即采取行动。
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