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ZENODO
Report . 2020
License: CC BY SA
Data sources: ZENODO
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ZENODO
Report . 2020
License: CC BY SA
Data sources: Datacite
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Data Study Group Final Report: WWF

Authors: Data Study Group Team;

Data Study Group Final Report: WWF

Abstract

Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the country’s top talent from data science, artificial intelligence, and wider fields, to analyse real-world data science challenges. Smart monitoring for conservation areas WWF (World Wide Fund for Nature) monitors over 250,000 protected areas (e.g. national parks and nature reserves) and thousands of other sites and critical habitats. These sites are the foundation of global natural assets and are central to the preservation of biodiversity and human well-being. Unfortunately, they face increasing pressures from human development. In this challenge, we explore various data science techniques to automatically detect news articles that report emerging threats to key protected areas. We describe a system that identifies such news stories near real-time. This is vital to enable the wider machinery of WWF and the conservation community to engage with governments, companies, shareholders, insurers, and others to help halt the degradation or destruction of key habitats.

Keywords

Natural language processing, WWF, Conservation, The Alan Turing Institute, Supervised learning, Neural networks, Data Study Groups, Habitats

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download
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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