Environmental & Animal Protection

Tracking trends of vegetarianism across China with data science

CEAP block lettering above Center for Environmental & Animal Protection on purple background

The objective of this team is to employ approaches from machine learning to collect, summarize, and analyze vegetarianism in China using alternative data. Leveraging natural language processing and computer vision, we gather data to track the distribution of meat-less diets throughout China, particularly cities like Shanghai. 

Among other goals, we build models to distinguish restaurants as vegetarian, non-vegetarian, or vegetarian friendly. We fit the models to data scraped from website, particularly food delivery apps. While we use frameworks to facilitate the training, validating, and testing of the models, we also need to collect, process, and label the data to incorporate into these frameworks.

Areas of Interest

  • Computer Science
  • Environmental Studies
  • Data Science

Methods & Technologies

  • Computer vision
  • Natural language processing
  • Deep learning
  • Data visualization
  • Web scraping

Partners

  • NYU Center for Data Science
  • NYU Center for Environmental & Animal Protection
  • NYU Courant Institute of Mathematical Sciences

Related Organizations

  • Good Food Summit
  • Berkeley Alt: Meat Lab

Faculty Advisor

  • Dr. Christopher Policastro
  • Email: christopher.policastro@nyu.edu