Literature DB >> 29528136

A framework for investigating illegal wildlife trade on social media with machine learning.

Enrico Di Minin1,2,3, Christoph Fink1,2, Tuomo Hiippala1,2,4, Henrikki Tenkanen1,2.   

Abstract

Article impact statement: Machine learning can be used to automatically monitor and assess illegal wildlife trade on social media platforms.
© 2018 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Entities:  

Mesh：

Year:  2018        PMID： 29528136     DOI： 10.1111/cobi.13104

Source DB:  PubMed          Journal:  Conserv Biol        ISSN： 0888-8892            Impact factor:   6.560


  3 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.  Analyzing the popularity of YouTube videos that violate mountain gorilla tourism regulations.

Authors:  Ryoma Otsuka; Gen Yamakoshi
Journal:  PLoS One       Date:  2020-05-21       Impact factor: 3.240

3.  Online media reveals a global problem of discarded containers as deadly traps for animals.

Authors:  Krzysztof Kolenda; Monika Pawlik; Natalia Kuśmierek; Adrian Smolis; Marcin Kadej
Journal:  Sci Rep       Date:  2021-01-11       Impact factor: 4.379
  3 in total

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