Update on the COVID-19 Digital Observatory

A few months ago we announced the launch of a COVID-19 Digital Observatory in collaboration with Pushshift and with funding from Protocol Labs. As part of this effort over the last several months, we have aggregated and published public data from multiple online communities and platforms. We’ve also been hard at work adding a series of new data sources that we plan to release in the near future.

Transmission electron microscope image of SARS-CoV-2—also known as 2019-nCoV, the not-so-novel-anymore virus that causes COVID-19 (Source: NIH NIAID via Wikimedia Commons, cc-sa 2.0)

More specifically, we have been gathering Search Engine Response Page (SERP) data on a range of COVID-19 related terms on a daily basis. This SERP data is drawn from both Bing and Google and has grown to encompass nearly 300GB of compressed data from four months of daily search engine results, with both PC and mobile results from nearly 500 different queries each day.

We have also continued to gather and publish revision and pageview data for COVID-related pages on English Wikipedia which now includes approximately 22GB of highly compressed data (several dozen gigabytes of compressed revision data each day) from nearly 1,800 different articles—a list that has been growing over time.

In addition, we are preparing releases of COVID-related data from Reddit and Twitter. We are almost done with two datasets from Reddit: a first one that includes all posts and comments from COVID-related subreddits, and a second that includes all posts or comments which include any of a set of COVID-related terms.

For the Twitter data, we are working out details of what exactly we will be able to release, but we anticipate including Tweet IDs and metadata for tweets that include COVID-related terms as well as those associated with hashtags and terms we’ve identified in some of the other data collection. We’re also designing a set of random samples of COVID-related Twitter content that will be useful for a range of projects.

In conjunction with these dataset releases, we have published all of the code to create the datasets as well as a few example scripts to help people learn how to load and access the data we’ve collected. We aim to extend these example analysis scripts in the future as more of the data comes online.

We hope you will take a look at the material we have been releasing and find ways to use it, extend it, or suggest improvements! We are always looking for feedback, input, and help. If you have a COVID-related dataset that you’d like us to publish, or if you would like to write code or documentation, please get in touch!

All of the data, code, and other resources are linked from the project homepage. To receive further updates on the digital observatory, you can also subscribe to our low traffic announcement mailing list.

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