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Plain Text - 17.5 KB - MD5: d9e139db4f19fc392ab3c0faeabbeda1
Plain Text - 756 B - MD5: ca9f7992171e7ebfd64a6314f651838d
Plain Text - 3.8 KB - MD5: 567b7563965b302c129259b8d2149fab
Jun 23, 2020
Runge, Claire A.; Daigle, Remi; Hausner, Vera H.; Monz, Christopher A., 2020, "Replication data for: Pan-Arctic analysis of cultural ecosystem services using social media and automated content analysis", https://doi.org/10.18710/DUANRP, DataverseNO, V1, UNF:6:ZahdAHYFWhoYLYqxvnk4bQ== [fileUNF]
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 o...
Tabular Data - 28.6 KB - 9 Variables, 368 Observations - UNF:6:aghwHPw5Ur35ztZApQuVHg==
Data on the percentage of photos that fall inside and outside protected areas, by country and ecosystem service group.
Tabular Data - 264.6 KB - 7 Variables, 6660 Observations - UNF:6:UqVJdclN5tT5yVIg2FjlfQ==
List of the labels assigned to photos by Google Cloud Vision and the corresponding ecosystem service group that we classified each into.
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