EbolaTracking and Zikatracking are two projects that aim to track the awareness about epidemic events in a georeferenced context and in real time. By tapping into the Twitter Streaming API and monitoring tweets mentioning epidemic-related keywords, the applications analyzes and classifies tweets using a machine learning system trained with the supervision of experts.

The data is the geolocalized matching geographical entities mentioned in tweets – such as country and city names – with the GeoNames database, and displayed on a map in order to shows events, i.e. groups of tweets that recently mentioned the same place. Blobs indicate mentioned places (not the place those tweets were posted from). Blob size relates to the frequency of recent mentions. Countries are color-coded to indicate country mentions. The user can than interact with specific locations to learn more about what is going on there.

EbolaTracking and ZikaTracking were designed and developed by the Data Science Laboratory of ISI Foundation (Marco Quaggiotto, André Panisson, Matteo Delfino, Ciro Cattuto, Daniela Paolotti, Michele Tizzoni) and in collaboration with the MoBS laboratory of Northeastern University (Nicola Perra, Qian Zhang, Alessandro Vespignani) with regard to EbolaTracking.