This challenge was designed specifically as a #ZindiWeekendz hackathon (COVID-19 Tweet Classification Challenge). We are re-opening the hackathon as a Knowledge Challenge, to allow the Zindi community to learn and test their skills. To help you all out, we’ve created a new Tutorials tab with helpful resources from the community. We encourage Zindians to share their code on the discussion board so that everyone in our community can learn from and support one another.
ML-driven sentiment analysis is an important tool to understand communities’ feelings around major issues such as COVID-19. Gathering comprehensive social data for sentiment analysis can be limited, however, if data collection relies only on keywords such as ‘coronavirus’ or ‘covid’.
The objective of this challenge is to develop a machine learning model to assess if a Twitter post is about COVID-19 or not. This model will help gather tweet data about the epidemic without relying only on key words like ‘covid’ or ‘coronavirus’ being present, allowing researchers and engineers to gather a more comprehensive dataset for sentiment analysis.
This model could be put into practice as part of a larger effort to understand online sentiment around COVID-19, and inform future communications and public interventions by governments and non-government public health organisations.
The Zindi community is joining the fight against COVID-19! #ZindiWeekendz are virtual weekend hackathons hosted by Zindi. This series of #ZindiWeekendz throughout April and May 2020 focuses specifically on COVID-19.
In a time of lockdowns, remote work, and general uncertainty, #ZindiWeekendz offer data scientists the opportunity to continue to develop their skills while contributing to practical, open-source AI solutions to help in the battle against COVID-19.
All winning solutions will be shared as a public good on GitHub. We are committed to supporting partners implement these solutions and encourage anyone who is interested to reach out to us at email@example.com.