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Digital Imaginations of National Parks in Different Social Media: A Data Exploration

Authors: Heikinheimo, Vuokko; Tenkanen, Henrikki; Hiippala, Tuomo; Toivonen, Tuuli;

Digital Imaginations of National Parks in Different Social Media: A Data Exploration

Abstract

Social media contains a wealth of information about human activities in different places. This information can complement data collection efforts in resource-scarce fields such as nature conservation. However, social media platforms differ in popularity, content, and access to data, and the choice of platform may greatly affect the resulting analysis. We explored Flickr, Instagram, and Twitter data from 39 Finnish national parks over a period of two years to assess the fitness-for-purpose of each platform for understanding place-based experiences of national park visitors. From Instagram, we extracted data using two different approaches: coordinate search and keyword search. Furthermore, we identified the languages used in Instagram data using the fastText library, and conducted preliminary content analysis of Flickr and Twitter data using Google Cloud Vision image annotation service. Instagram was the most popular platform in all national parks. Noteworthy, almost 50% of Twitter users had shared their geotagged national park post to Twitter via Instagram. Language identification from text content and content analysis of images provide basis for further exploration of the digital representations of national parks and place-related experiences of visitors.

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Keywords

Computer and information sciences, content analysis, social media, Twitter, GIScience, Environmental sciences, national parks, Instagram, Flickr

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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!
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