CovidTracker: A comprehensive Covid-related social media dataset for NLP tasks

Abstract: The Covid-19 pandemic presented an unprecedented global public health emergency, and concomitantly an unparalleled opportunity to investigate public responses to adverse social conditions. The widespread ability to post messages to social media platforms provided an invaluable outlet for such an outpouring of public sentiment, including not only expressions of social solidarity, but also the spread of misinformation and misconceptions around the effect and potential risks of the pandemic. This archive of message content therefore represents a key resource in understanding public responses to health crises, analysis of which could help to inform public policy interventions to better respond to similar events in future. We present a benchmark database of public social media postings from the United Kingdom related to the Covid-19 pandemic for academic research purposes, along with some initial analysis, including a taxonomy of key themes organised by keyword. This release supports the findings of a research study funded by the Scottish Government Chief Scientists' Office that aims to investigate social sentiment in order to understand the response to public health measures implemented during the pandemic.