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Mapping wildlife species distribution with social media: Augmenting text classification with species names

Jeawak, Shelan, Jones, Christopher and Schockaert, Steven 2018. Mapping wildlife species distribution with social media: Augmenting text classification with species names. Presented at: GIScience 2018: 10th International Conference on Geographic Information Science, Melbourne, Australia, 28-31 August 2018. Published in: Winter, Stephan, Griffin, Amy and Sester, Monika eds. 10th International Conference of Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs) Dagstuhl, Germany: Schloss Dagstuhl/Leibniz-Zentrum fuer Informatik, 34:1-34:6. 10.4230/LIPIcs.GISCIENCE.2018.34

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Abstract

Social media has considerable potential as a source of passive citizen science observations of the natural environment, including wildlife monitoring. Here we compare and combine two main strategies for using social media postings to predict species distributions: (i) identifying postings that explicitly mention the target species name and (ii) using a text classifier that exploits all tags to construct a model of the locations where the species occurs. We find that the first strategy has high precision but suffers from low recall, with the second strategy achieving a better overall performance. We furthermore show that even better performance is achieved with a meta classifier that combines data on the presence or absence of species name tags with the predictions from the text classifier.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: Schloss Dagstuhl/Leibniz-Zentrum fuer Informatik
ISBN: 978-3-95977-083-5
ISSN: 1868-8969
Date of First Compliant Deposit: 18 July 2018
Last Modified: 29 Aug 2019 21:25
URI: http://orca-mwe.cf.ac.uk/id/eprint/112684

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