Literature DB >> 29335570

Machine learning for tracking illegal wildlife trade on social media.

Enrico Di Minin1,2, Christoph Fink3, Henrikki Tenkanen3, Tuomo Hiippala3,4.   

Abstract

Mesh：

Year:  2018        PMID： 29335570     DOI： 10.1038/s41559-018-0466-x

Source DB:  PubMed          Journal:  Nat Ecol Evol        ISSN： 2397-334X            Impact factor:   15.460


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  5 in total

1.  Concerned or Apathetic? Using Social Media Platform (Twitter) to Gauge the Public Awareness about Wildlife Conservation: A Case Study of the Illegal Rhino Trade.

Authors:  Siqing Shan; Xijie Ju; Yigang Wei; Xin Wen
Journal:  Int J Environ Res Public Health       Date:  2022-06-03       Impact factor: 4.614

2.  Sharing for science: high-resolution trophic interactions revealed rapidly by social media.

Authors:  Robin A Maritz; Bryan Maritz
Journal:  PeerJ       Date:  2020-07-09       Impact factor: 2.984

3.  A Graph Theory approach to assess nature's contribution to people at a global scale.

Authors:  Silvia de Juan; Andrés Ospina-Álvarez; Sebastián Villasante; Ana Ruiz-Frau
Journal:  Sci Rep       Date:  2021-04-27       Impact factor: 4.379

4.  Detecting the Severity of Socio-Spatial Conflicts Involving Wild Boars in the City Using Social Media Data.

Authors:  Małgorzata Dudzińska; Agnieszka Dawidowicz
Journal:  Sensors (Basel)       Date:  2021-12-08       Impact factor: 3.576

5.  Wildlife trade shifts from brick-and-mortar markets to virtual marketplaces: A case study of birds of prey trade in Thailand.

Authors:  Penthai Siriwat; Vincent Nijman
Journal:  J Asia Pac Biodivers       Date:  2020-03-25
  5 in total

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