Experts combating wildlife trafficking manually sift through articles about seizures and arrests, which is time consuming and makes identifying trends difficult. In this project, we applied natural language processing techniques to extract data from reports published by the Eco Activists for Governance and Law Enforcement. We expanded on spaCy’s pre-trained pipeline and added custom named entities which enabled us to identify approximately 40% of wildlife trafficking events. We created visualizations to display trends in the extracted data, which are accessible on our website, Wildlife Trafficking in Africa. This project is an initial solution to automatically extract, collect, and display, wildlife trafficking data for experts to easily analyze.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Grasso, Victoria
• Gagnon, Maylee
• Coughlin, Devin

Publisher

• Worcester Polytechnic Institute

Identifier

• 49866
• E-project-030622-185417

Keyword

• NLP
• Wildlife Trafficking

Advisor

• Konrad, Renata
• Lee, Kyumin

Year

• 2022

Sponsor

• Patricia Raxter
• Meredith Gore

Date created

• 2022-03-06

Resource type

• Major Qualifying Project

Major

• Computer Science

Rights statement

• In Copyright