EDNA-Covid: A Large-Scale Covid-19 Tweets Dataset Collected with the EDNA Streaming Toolkit

Suprem, Abhijit; Pu, Calton

The Covid-19 pandemic has fundamentally altered many facets of our lives. With nationwide lockdowns and stay-at-home advisories, conversations about the pandemic have naturally moved to social networks, e.g. Twitter. This affords an unprecedented insight into the evolution of social discourse in the presence of a long-running destabilizing factor such as a pandemic with the high-volume, high-velocity, high-noise Covid-19 Twitter feed. However, real-time information extraction from such a data stream requires a fault-tolerant streaming infrastructure to perform the non-trivial integration of heterogenous data sources from news organizations, social feeds, and authoritative medical organizations like the CDC. To address this, we present (i) the EDNA streaming toolkit for consuming and processing streaming data, and (ii) EDNA-Covid, a multilingual, large-scale dataset of coronavirus-related tweets collected with EDNA since January 25, 2020. EDNA-Covid includes, at time of this publication, over 600M tweets from around the world in over 10 languages. We release both the EDNA toolkit and the EDNA-Covid dataset to the public so that they can be used to extract valuable insights on this extraordinary social event.