In this study, we provide a replicable, data-driven approach to investigate a potential second wave of the COVID pandemic. In an open science spirit, we are particularly interested in how citizens can take part in research projects at all levels, from crowdsourcing to machine learning algorithms.
This is why we tried to open the products of this study as much as possible, from downloadable labeling data to directly editable notebooks through Binder.
Data & Privacy
We collected tweets specifically from users in Île-de-France. We first used the Streaming API to identify users in the Paris area, and then collected the historic data from these users. This dashboard presents our analyses, based on 30,000 Twitter users, for a total of about 33 million tweets from December 2019 (17 million without retweets).
For the number of passages to emergencies, we used public data from Santé Publique France about emergencies and SOS Médecins data related to COVID.
This website does not store any personal identifiable information.
If you are annotating tweets, the only thing being stored is a random but
unique identifier tied to your current browser that will be associated with your annotations.
Additionally, this site's hoster Heroku stores and gives us access to the IP addresses of visitors and the pages visited on this site. These logs are stored by them for up to a week.
Team leader of the Interaction Data Lab, CRI Research Fellow and Director of Research for Just One Giant Lab.Learn more