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

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

© 2018 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Bibliographische Detailangaben
Veröffentlicht in:Conservation biology : the journal of the Society for Conservation Biology. - 1989. - 33(2019), 1 vom: 05. Feb., Seite 210-213
1. Verfasser: Di Minin, Enrico (VerfasserIn)
Weitere Verfasser: Fink, Christoph, Hiippala, Tuomo, Tenkanen, Henrikki
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2019
Zugriff auf das übergeordnete Werk:Conservation biology : the journal of the Society for Conservation Biology
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
Beschreibung
Zusammenfassung:© 2018 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.
Article impact statement: Machine learning can be used to automatically monitor and assess illegal wildlife trade on social media platforms
Beschreibung:Date Completed 17.10.2019
Date Revised 25.07.2020
published: Print-Electronic
Citation Status MEDLINE
ISSN:1523-1739
DOI:10.1111/cobi.13104