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Dataset Persistent ID
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doi:10.18710/DUANRP |
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Publication Date
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2020-06-23 |
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Title
| Replication data for: Pan-Arctic analysis of cultural ecosystem services using social media and automated content analysis |
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Author
| Runge, Claire A. (UiT The Arctic University of Norway) - ORCID: 0000-0003-3913-8560
Daigle, Remi (Département de biologie, Université Laval, Québec, Canada)
Hausner, Vera H. (UiT The Arctic University of Norway) - ORCID: 0000-0001-9825-0419
Monz, Christopher A. (Department of Environment and Society and the Ecology Center, Utah State University)
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Contact
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Use email button above to contact.
Runge, Claire A. (UiT The Arctic University of Norway)
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Description
| In the Arctic, as in many parts of the world, interactions with the natural world are an important part of people’s experience and are often recorded in photographs. Emerging methods for automated content analysis of social media data offers opportunities to discover information on cultural ecosystem services from photographs across large samples of people and countries. We analysed over 800,000 Flickr photographs using Google’s Cloud Vision algorithm to identify the components of the natural environment most photographed and to map how and where different people interact with nature across eight Arctic countries. Almost all (91.1%) of users took one or more photographs of biotic nature, and such photos account for over half (53.2 %) of Arctic photos on Flickr. We find that although the vast majority of Arctic human-nature interactions occur outside protected areas, people are slightly more likely to photograph nature inside protected areas after accounting for the low accessibility of Arctic protected areas. Wildlife photographers travel further from roads than people who take fewer photographs of wildlife, and people venture much further from roads inside protected areas. A large diversity of nature was reflected in the photographs, from mammals, birds, fish, fungi, plants and invertebrates, signalling an untapped potential to connect and engage people in the appreciation and conservation of the natural world. Our findings suggest that, despite limitations, automated content analysis can be a rapid and readily accessed source of data on how and where people interact with nature, and a large-scale method for assessing cultural ecosystem services across countries and cultures. (2019-03-22)
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Subject
| Earth and Environmental Sciences; Social Sciences |
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Keyword
| Arctic
cultural ecosystem services
nature
photography
biodiversity
tourism
ecotourism
passive crowdsourcing
social media
Flickr
Google Cloud Vision
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Related Publication
| Runge, Claire A., Hausner, Vera H., Daigle, Remi M., and Monz, Christopher A. 2020. Pan-Arctic analysis of cultural ecosystem services using social media and automated content analysis. Environmental Research Communications (in press) doi: 10.1088/2515-7620/ab9c33 https://doi.org/10.1088/2515-7620/ab9c33
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Language
| English |
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Producer
| UiT The Arctic University of Norway (UiT) https://en.uit.no/
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Grant Information
| FRAM: RConnected
Arctic Belmont Forum: CONNECT
Norwegian Research Council: 247474
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Distributor
| UiT Open Research Data (UiT The Arctic University of Norway) http://opendata.uit.no/
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Depositor
| Runge, Claire Alice |
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Deposit Date
| 2019-03-22 |
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Time Period Covered
| Start: 2004-01-01 ; End: 2017-12-31
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Date of Collection
| Start: 2017-04-12 ; End: 2018-05-07
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Kind of Data
| Metadata associated with geotagged photographs |
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Data Sources
| www.flickr.com https://cloud.google.com/vision/ |
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Documentation and Access to Sources
| https://www.flickr.com/services/api/ https://cloud.google.com/vision/docs/labels |
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