Citation
American Psychological Association 7th edition (APA 7th)
🇺🇸 English, US
Casas, J., Mugellini, E., & Abou Khaled, O. (2020). Early Detection of Foodborne Illnesses in Social Media. In Advances in Intelligent Systems and Computing (pp. 415–420). Springer International Publishing. https://doi.org/10.1007/978-3-030-44267-5_62
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Résumé
Alert Center is a platform aiming at detecting outbreaks caused by food toxin infections and food intoxications in Switzerland. It does this by analyzing tweets and sending alerts to the Federal Food Safety and Veterinary Office (FSVO) when a risk is detected. The platform is composed of four main parts: a real-time extractor that targets tweets based on a list of curated keywords, three classifiers (one for each main spoken language) that isolate tweets related to food toxin, a system that locates tweets on the Swiss territory and a web-based dashboard to visualize the results. Combining localization algorithms of tweets and users allows the system to locate 75.09% of the tweets, 2.31% of which were located in Switerzland. In addition, a list of Swiss Twitter accounts corresponding to 15% of the total estimated number of Swiss accounts has been created.