A protocol for harvesting biodiversity data from Facebook

Bibliographische Detailangaben
Veröffentlicht in:	Conservation biology : the journal of the Society for Conservation Biology. - 1999. - 38(2024), 4 vom: 29. Juli, Seite e14257
1. Verfasser:	Chowdhury, Shawan (VerfasserIn)
Weitere Verfasser:	Ahmed, Sultan, Alam, Shofiul, Callaghan, Corey T, Das, Priyanka, Di Marco, Moreno, Di Minin, Enrico, Jarić, Ivan, Labi, Mahzabin Muzahid, Rokonuzzaman, Md, Roll, Uri, Sbragaglia, Valerio, Siddika, Asma, Bonn, Aletta
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2024
Zugriff auf das übergeordnete Werk:	Conservation biology : the journal of the Society for Conservation Biology
Schlagworte:	Journal Article Bangladesh Facebook Wallacean shortfall ciencia ciudadana citizen science colaboración masiva crowdsourcing déficit wallaceano iEcology mehr... megadiverse countries países megadiversos redes sociales social media tropics trópicos

Beschreibung
Zusammenfassung:	© 2024 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology. The expanding use of community science platforms has led to an exponential increase in biodiversity data in global repositories. Yet, understanding of species distributions remains patchy. Biodiversity data from social media can potentially reduce the global biodiversity knowledge gap. However, practical guidelines and standardized methods for harvesting such data are nonexistent. Following data privacy and protection safeguards, we devised a standardized method for extracting species distribution records from Facebook groups that allow access to their data. It involves 3 steps: group selection, data extraction, and georeferencing the record location. We present how to structure keywords, search for species photographs, and georeference localities for such records. We further highlight some challenges users might face when extracting species distribution data from Facebook and suggest solutions. Following our proposed framework, we present a case study on Bangladesh's biodiversity-a tropical megadiverse South Asian country. We scraped nearly 45,000 unique georeferenced records across 967 species and found a median of 27 records per species. About 12% of the distribution data were for threatened species, representing 27% of all species. We also obtained data for 56 DataDeficient species for Bangladesh. If carefully harvested, social media data can significantly reduce global biodiversity knowledge gaps. Consequently, developing an automated tool to extract and interpret social media biodiversity data is a research priority
Beschreibung:	Date Completed 23.07.2024 Date Revised 23.07.2024 published: Print-Electronic Citation Status MEDLINE
ISSN:	1523-1739
DOI:	10.1111/cobi.14257