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DOI: 10.4230/LIPIcs.GISCIENCE.2018.34

Mapping Wildlife Species Distribution With Social Media: Augmenting Text Classification With Species Names (Short Paper)

Authors: Shelan S. Jeawak, Christopher B. Jones, and Steven Schockaert

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)

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.

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Shelan S. Jeawak, Christopher B. Jones, and Steven Schockaert. Mapping Wildlife Species Distribution With Social Media: Augmenting Text Classification With Species Names (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 34:1-34:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{jeawak_et_al:LIPIcs.GISCIENCE.2018.34,
  author =	{Jeawak, Shelan S. and Jones, Christopher B. and Schockaert, Steven},
  title =	{{Mapping Wildlife Species Distribution With Social Media: Augmenting Text Classification With Species Names}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{34:1--34:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.34},
  URN =		{urn:nbn:de:0030-drops-93626},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.34},
  annote =	{Keywords: Social media, Text mining, Volunteered Geographic Information, Ecology}
}

Document

DOI: 10.4230/LIPIcs.COSIT.2017.21

Using Flickr for Characterizing the Environment: An Exploratory Analysis

Authors: Shelan S. Jeawak, Christopher B. Jones, and Steven Schockaert

Published in: LIPIcs, Volume 86, 13th International Conference on Spatial Information Theory (COSIT 2017)

Abstract

The photo-sharing website Flickr has become a valuable informal information source in disciplines such as geography and ecology. Some ecologists, for instance, have been manually analysing Flickr to obtain information that is more up-to-date than what is found in traditional sources. While several previous works have shown the potential of Flickr tags for characterizing places, it remains unclear to what extent such tags can be used to derive scientifically useful information for ecologists in an automated way. To obtain a clearer picture about the kinds of environmental features that can be modelled using Flickr tags, we consider the problem of predicting scenicness, species distribution, land cover, and several climate related features. Our focus is on comparing the predictive power of Flickr tags with that of structured data from more traditional sources. We find that, broadly speaking, Flickr tags perform comparably to the considered structured data sources, being sometimes better and sometimes worse. Most importantly, we find that combining Flickr tags with structured data sources consistently, and sometimes substantially, improves the results. This suggests that Flickr indeed provides information that is complementary to traditional sources.

Cite as

Shelan S. Jeawak, Christopher B. Jones, and Steven Schockaert. Using Flickr for Characterizing the Environment: An Exploratory Analysis. In 13th International Conference on Spatial Information Theory (COSIT 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 86, pp. 21:1-21:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{jeawak_et_al:LIPIcs.COSIT.2017.21,
  author =	{Jeawak, Shelan S. and Jones, Christopher B. and Schockaert, Steven},
  title =	{{Using Flickr for Characterizing the Environment: An Exploratory Analysis}},
  booktitle =	{13th International Conference on Spatial Information Theory (COSIT 2017)},
  pages =	{21:1--21:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-043-9},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{86},
  editor =	{Clementini, Eliseo and Donnelly, Maureen and Yuan, May and Kray, Christian and Fogliaroni, Paolo and Ballatore, Andrea},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2017.21},
  URN =		{urn:nbn:de:0030-drops-77523},
  doi =		{10.4230/LIPIcs.COSIT.2017.21},
  annote =	{Keywords: Social media, Volunteered Geographic Information, Ecology}
}

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Documents authored by Jeawak, Shelan S.

Mapping Wildlife Species Distribution With Social Media: Augmenting Text Classification With Species Names (Short Paper)

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Using Flickr for Characterizing the Environment: An Exploratory Analysis

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