Research Paper: Restaurant Closures during the COVID-19 Pandemic: A Descriptive Analysis

I’ve had a handful of Community members reach out about other research looking at restaurant closures recently!

Wanted to show this paper by Dmitry Sedov! In this work, SafeGraph data is combined with Yelp data to learn about restaurant closures during the first year of the COVID-19 pandemic. They find that distance from city center, amount of nearby other establishments, Yelp rating, and number of Yelp reviews provide lift in assessing restaurant closure likelihood. Closure rates varied widely from city to city, with Honolulu’s exit rate on the high end at 21.5% and El Paso’s on the low end at 9.6%.

:point_right:Check out the full publication here! :point_left:

This is an excellent example of the value of joining datasets! SafeGraph and Yelp data are cool on their own, but their power grows exponentially when joined.


This topic was automatically generated from Slack. You can find the original thread here.

Another great publication to check out would be this one by @Zhengtian_Xu_George_Washington_University - here’s the original post: