Camryn Bell on Algorithmic Gentrification with Will Payne

08 Jun, 2019

Camryn Bell on Algorithmic Gentrification with Will Payne

The BCNM is pleased to offer several undergraduate research fellowships each year. Undergraduates are paired with our graduate students, who mentor them in research methodology. This year, Camryn Bell worked on Will Payne's Algorithmic Gentrification. Read more about her experience below.

This semester, I served as a research assistant to Will Payne on his project “Algorithmic Gentrification,” doing work related to his larger dissertation work on how digital location-based services have shaped urban consumption spaces and neighborhoods.

In my time on the project, I engaged with various sub-projects largely involved in building and cleaning up data sets taken from Zagat Restaurant Guides. My first task was geocoding restaurant locations in order to get an accurate read on where places were located, which initially presented some issues in the cases of restaurant closures or moves. However, with a little bit of digging via Google and Google Maps, I would come across the correct locations and add them to the larger data set. I also worked on data correction for restaurant listings, going through to see where the scanned material from the guides may have been incorrect in places and correcting where necessary. Another smaller project I worked on during the semester was editing code for the project, including adding cuisine tags for some of the years of the Zagat guides we looked at. This made for a clean script to use to parse out the sort of categorizations restaurants were falling into. I am still wrapping up some of the final code editing, and this last task entails going through the script and finding discrepancies between the restaurant spellings in the guides and the code output. This typically involves going through things such as abbreviations or inconsistencies in how the names are listed.

Some highlights of this project have been familiarizing myself with the restaurant scene in New York City and getting to know the places reviewed in the guides, even if some of this knowledge is now a little outdated. I’ve also enjoyed seeing some of the more ridiculous restaurant titles during my research, which has kept going through the data interesting (see: “A Salt & Battery,” a fish ‘n’ chips restaurant with locations on the East Side and in the West Village). In a similar vein, some of the reviews have also been quite funny and sometimes cringey, but always entertaining to read. And finally, in line with the broader goals of the project, I also appreciated getting a view at how the restaurant scene has changed over the years and what sort of trends and changes have occured in the time periods we looked at. Overall, this project was a great primer in working through data sets, and truly expanded my perspective on how to utilize data from a nontraditional source like the Zagat guides.