Web Data Mining and Social Media Analysis for better Communication in Food Safety Crises

Abstract

Although much effort is made to prevent risks arising from food, food-borne diseases are an ever-present threat to the consumers’ health. The consumption of fresh food that is contaminated with pathogens like fungi, viruses or bacteria can cause food poisoning that leads to severe health damages or even death. The outbreak of Shiga Toxin-producing enterohemorrhagic E. coli (EHEC) in Germany and neighbouring countries in 2011 has shown this dramatically. Nearly 4.000 people were reported of being affected and more than 50 people died during the so called EHEC-crisis. As a result the consumers’ trust in the safety of fruits and vegetables decreased sharply.
In situations like that quick decisions and reaction from public authorities as well as from privately owned companies are important: Food crisis managers have to identify and track back contaminated products and they have to withdraw them from the market. At the same time they have to inform the stakeholders about potential threats and recent developments. This is a particularly challenging task, because when an outbreak is just detected, information about the actual scope is sparse and the demand for information is high. Thus, ineffective communication among crisis managers and towards the public can result in inefficient crisis management, health damages and a major loss of trust in the food system. This is why crisis communication is a crucial part of successful crisis management, whereas the quality of crisis communication largely depends on the availability of and the access to relevant information.
In order to improve the availability of information, we have explored how information from public accessible internet sources like Twitter or Wikipedia can be harnessed for food crisis communication. In this paper we are going to report on some initial insight from a web mining and social media analysis approach to monitor health and food related issues that can develop into a potential crisis. We have chosen Twitter and Wikipedia as data sources for our study since they’re publicly accessible and reveal what people state about certain topics and what they are looking for in order to answer their questions.