A protocol for harvesting biodiversity data from Facebook

The expanding use of community science platforms has led to an exponential increase inbiodiversity data in global repositories. Yet, understanding of species distributions remainspatchy. Biodiversity data from social media can potentially reduce the global biodiversityknowledge gap. However, practical guidelines and standardized methods for harvestingsuch data are nonexistent. Following data privacy and protection safeguards, we deviseda standardized method for extracting species distribution records from Facebook groupsthat allow access to their data. It involves 3 steps: group selection, data extraction, andgeoreferencing the record location. We present how to structure keywords, search forspecies photographs, and georeference localities for such records. We further highlightsome challenges users might face when extracting species distribution data from Facebookand suggest solutions. Following our proposed framework, we present a case study onBangladesh’s biodiversity—a tropical megadiverse South Asian country. We scraped nearly45,000 unique georeferenced records across 967 species and found a median of 27 recordsper species. About 12% of the distribution data were for threatened species, representing27% of all species. We also obtained data for 56 DataDeficient species for Bangladesh. Ifcarefully harvested, social media data can significantly reduce global biodiversity knowledg gaps. Consequently, developing an automated tool to extract and interpret social mediabiodiversity data is a research priority.