文章基本信息

标题：Mapping Wildlife Species Distribution With Social Media: Augmenting Text Classification With Species Names (Short Paper)
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作者：Shelan S. Jeawak ; Christopher B. Jones ; Steven Schockaert 等
期刊名称：LIPIcs : Leibniz International Proceedings in Informatics
电子版ISSN：1868-8969
出版年度：2018
卷号：114
页码：1-6
DOI：10.4230/LIPIcs.GISCIENCE.2018.34
出版社：Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
摘要：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.
关键词：Social media; Text mining; Volunteered Geographic Information; Ecology