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A guide to using the internet to monitor and quantify the wildlife trade
Author(s) -
Stringham Oliver C.,
Toomes Adam,
Kanishka Aurelie M.,
Mitchell Lewis,
Heinrich Sarah,
Ross Joshua V.,
Cassey Phillip
Publication year - 2021
Publication title -
conservation biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.2
H-Index - 222
eISSN - 1523-1739
pISSN - 0888-8892
DOI - 10.1111/cobi.13675
Subject(s) - wildlife , the internet , wildlife trade , social media , law enforcement , computer science , discoverability , business , world wide web , data science , ecology , political science , biology , law
The unrivaled growth in e‐commerce of animals and plants presents an unprecedented opportunity to monitor wildlife trade to inform conservation, biosecurity, and law enforcement. Using the internet to quantify the scale of the wildlife trade (volume and frequency) is a relatively recent and rapidly developing approach that lacks an accessible framework for locating relevant websites and collecting data. We produced an accessible guide for internet‐based wildlife trade surveillance. We detailed a repeatable method involving a systematic internet search, with search engines, to locate relevant websites and content. For data collection, we highlight web‐scraping technology as an efficient way to collect data in an automated fashion at regularly timed intervals. Our guide is applicable to the multitude of trade‐based contexts because researchers can tailor search keywords for specific taxa or derived products and locations of interest. We provide information for working with the diversity of websites used in wildlife trade. For example, to locate relevant content on social media (e.g., posts or groups), each social media platform should be examined individually via the site's internal search engine. A key advantage of using the internet to study wildlife trade is the relative ease of access to an increasing amount of trade‐related data. However, not all wildlife trade occurs online and it may occur on unobservable sections of the internet.