Text Mining & Analysis

This page is dedicated to the 'Text mining & Analysis' division of the CoVid 2019-Biohackathon 2020.

Rich analyses shall be done, explanatory visualizations & dashboard shall be made, datasets shall be curated & maintained for future scientific research projects.

Research hypotheses & mini-publications are invited in the realms of:

Transmission, incubation, and environmental stability of SARS-COV-2

Risk factors for CoVid 2019

Genetics, origin, and evolution of SARS-COV-2

Therapeutics & Vaccines against SARS-COV-2

Health systems' capacity to deal with the CoVid 2019 pandemic

Non-pharmaceutical interventions against the CoVid 2019 pandemic

Diagnostics & Surveillance against the CoVid 2019 pandemic

Information sharing and Inter-sectoral collaboration against the CoVid 2019 pandemic

Ethical and social science considerations related to dealing with & combating against the CoVid 2019 pandemic

Paul Mooney's elaborative schema, breaking down the 'tasks' of COVID-19 Open Research Dataset Challenge (CORD-19): An AI challenge with AI2, CZI, MSR, Georgetown, NIH & The White House to the minute significant details will guide you further.

Twitter data analysis using (https://zenodo.org/record/3735274).

Potential tasks:

• Identification of symptoms on Twitter users - Quantify how many users are claiming symptoms.
• Identification of potential persons that have recovered - We only know the number of people that recover from hospitals, what about outside of them? Are people talking about this on Twitter?
• Sentiment analysis towards particular regulations such as social distancing measures - How are these measures perceived over time in the Twitter space.

Characterize the information/misinformation around potential COVID-19 treatments using Twitter data

Communication

Join the Slack workspace & head on to to 'text-mining-and-analysis' channel. It shall be fun.

#Participants

• Ali Haider Bangash (coordinator)
• Juan M. Banda - Twitter data analysis
• Thanasis Vergoulis
• [Ramya Tekumalla] (https://github.com/tramya28)