The Food Sentiment Observatory: Exploiting New Forms of Data to Help Inform Policy on Food Safety & Food Crime Risks

食品情绪观察站：利用新形式的数据来帮助制定食品安全政策

• 批准号: ES/P011004/1
• 负责人: Peter Edwards
• 金额: $ 20.47万
• 依托单位: University of Aberdeen
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FP011004%2F1
• 关键词: Food; Sentiment; Observatory; Exploiting; New

Social media and other forms of online content have enormous potential as a way to understand people's opinions and attitudes, and as a means to observe emerging phenomena - such as disease outbreaks. How might policy makers use such new forms of data to better assess existing policies and help formulate new ones? This one year demonstrator project is a partnership between computer science academics at the University of Aberdeen and officers from Food Standards Scotland which aims to answer this question. Food Standards Scotland is the public-sector food body for Scotland created by the Food (Scotland) Act 2015. It regularly provides policy guidance to ministers in areas such as food hygiene monitoring and reporting, food-related health risks, and food fraud.The project will develop a software tool (the Food Sentiment Observatory) that will be used to explore the role of data from sources such as Twitter, Facebook, and TripAdvisor in three policy areas selected by Food Standards Scotland:- attitudes to the differing food hygiene information systems used in Scotland and the other UK nations; - study of an historical E.coli outbreak associated with venison products to understand effectiveness of monitoring and decision making protocols; - understanding the potential role of social media data in responding to new and emerging forms of food fraud.The Observatory will integrate a number of existing software tools (developed in our recent research) to allow us to mine large volumes of data to identify important textual signals, extract opinions held by individuals or groups, and crucially, to document these data processing operations - to aid transparency of policy decision-making. Given the amount of noise appearing in user-generated online content (such as fake restaurant reviews) it is our intention to investigate methods to extract meaningful and reliable knowledge, to better support policy making.

社交媒体和其他形式的在线内容作为了解人们的观点和态度的一种方式，以及作为观察新现象（如疾病爆发）的一种手段，具有巨大的潜力。政策制定者如何使用这种新形式的数据来更好地评估现有政策并帮助制定新政策？这个为期一年的示范项目是阿伯丁大学计算机科学学者和苏格兰食品标准局官员之间的合作项目，旨在回答这个问题。苏格兰食品标准局是根据《2015年苏格兰食品法》设立的苏格兰公共部门食品机构。它定期在食品卫生监测和报告、与食品有关的健康风险和食品欺诈等领域向部长们提供政策指导。该项目将开发一种软件工具（食品情绪观察站），用于探索来自Twitter、Facebook和TripAdvisor等来源的数据在苏格兰食品标准局选择的三个政策领域中的作用：对苏格兰和其他英国国家使用的不同食品卫生信息系统的态度；-研究历史上与鹿肉产品有关的大肠杆菌爆发，以了解监测和决策协议的有效性；-了解社交媒体数据在应对新兴食品欺诈形式方面的潜在作用。天文台将整合多个现有的软件工具（在我们最近的研究中开发的），使我们能够挖掘大量数据，以识别重要的文本信号，提取个人或团体的意见，最重要的是，记录这些数据处理操作，以提高政策制定的透明度。考虑到用户生成的在线内容（如虚假的餐厅评论）中出现的噪音数量，我们打算研究提取有意义和可靠知识的方法，以更好地支持政策制定。

项目成果

Encyclopedia of Social Network Analysis and Mining (2nd Edition)

社交网络分析与挖掘百科全书（第二版）

• 发表时间: 2017
• 作者: Yusof N.