February 26, 2026
Tracking Wildlife Trafficking in the Age of Online Marketplaces
News2026-02-26
A team of researchers led by VIDA Center Co-director Juliana Freire is using data science to track — and combat — the illegal animal trade.
Wildlife trafficking is one of the world’s most widespread illegal trades, contributing to biodiversity loss, organized crime, and public health risks. Once concentrated in physical markets, much of this activity has moved online. Today, animals and animal products are advertised on large e-commerce platforms alongside ordinary consumer goods. This shift makes enforcement harder — but it also creates a valuable source of data.
Every online advertisement leaves behind digital information: text descriptions, prices, images, seller details, and timestamps. If collected and analyzed at scale, these traces can help researchers understand how wildlife trafficking operates online. The problem is volume. Online marketplaces contain millions of listings, and most searches for animal names return irrelevant results such as toys, artwork, or souvenirs. Distinguishing illegal wildlife ads from harmless products is difficult to do manually and challenging to automate.
Institute Professor of Computer Science Juliana Freire is part of a team that is taking on the problem head on, building a scalable system designed to address this challenge. They developed a flexible data collection pipeline that automatically gathers wildlife-related advertisements from the web and filters them using modern machine learning techniques. The goal is not to focus on one species or one website, but to enable broad, systematic monitoring across many platforms, regions, and languages, as well as to develop strategies to disrupt illegal markets.
The team is a multi-disciplinary effort, including Gohar Petrossian, Professor of Criminal Justice at John Jay College of Criminal Justice; Jennifer Jacquet, Professor of Environmental Science and Policy at the University of Miami; and Sunandan Chakraborty, Professor of Data Science at Indiana University.
Every online advertisement leaves behind digital information: text descriptions, prices, images, seller details, and timestamps. If collected and analyzed at scale, these traces can help researchers understand how wildlife trafficking operates online. The problem is volume. Online marketplaces contain millions of listings, and most searches for animal names return irrelevant results such as toys, artwork, or souvenirs. Distinguishing illegal wildlife ads from harmless products is difficult to do manually and challenging to automate.
Institute Professor of Computer Science Juliana Freire is part of a team that is taking on the problem head on, building a scalable system designed to address this challenge. They developed a flexible data collection pipeline that automatically gathers wildlife-related advertisements from the web and filters them using modern machine learning techniques. The goal is not to focus on one species or one website, but to enable broad, systematic monitoring across many platforms, regions, and languages, as well as to develop strategies to disrupt illegal markets.
The team is a multi-disciplinary effort, including Gohar Petrossian, Professor of Criminal Justice at John Jay College of Criminal Justice; Jennifer Jacquet, Professor of Environmental Science and Policy at the University of Miami; and Sunandan Chakraborty, Professor of Data Science at Indiana University.