Social media data for conservation science : A methodological overview

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Toivonen , T , Heikinheimo , V , Fink , C , Hausmann , A , Hiippala , T , Järv , O , Tenkanen , H & Di Minin , E 2019 , ' Social media data for conservation science : A methodological overview ' , Biological Conservation , vol. 233 , pp. 298-315 . https://doi.org/10.1016/j.biocon.2019.01.023

Title: Social media data for conservation science : A methodological overview
Author: Toivonen, Tuuli; Heikinheimo, Vuokko; Fink, Christoph; Hausmann, Anna; Hiippala, Tuomo; Järv, Olle; Tenkanen, Henrikki; Di Minin, Enrico
Contributor: University of Helsinki, Helsinki Institute of Sustainability Science (HELSUS)
University of Helsinki, Helsinki Institute of Sustainability Science (HELSUS)
University of Helsinki, Helsinki Institute of Sustainability Science (HELSUS)
University of Helsinki, Department of Geosciences and Geography
University of Helsinki, English Philology
University of Helsinki, Department of Geosciences and Geography
University of Helsinki, Helsinki Institute of Sustainability Science (HELSUS)
University of Helsinki, Helsinki Institute of Sustainability Science (HELSUS)
Date: 2019-05
Language: eng
Number of pages: 18
Belongs to series: Biological Conservation
ISSN: 0006-3207
URI: http://hdl.handle.net/10138/300749
Abstract: Improved understanding of human-nature interactions is crucial to conservation science and practice, but collecting relevant data remains challenging. Recently, social media have become an increasingly important source of information on human-nature interactions. However, the use of advanced methods for analysing social media is still limited, and social media data are not used to their full potential. In this article, we present available sources of social media data and approaches to mining and analysing these data for conservation science. Specifically, we (i) describe what kind of relevant information can be retrieved from social media platforms, (ii) provide a detailed overview of advanced methods for spatio-temporal, content and network analyses, (iii) exemplify the potential of these approaches for real-world conservation challenges, and (iv) discuss the limitations of social media data analysis in conservation science. Combined with other data sources and carefully considering the biases and ethical issues, social media data can provide a complementary and cost-efficient information source for addressing the grand challenges of biodiversity conservation in the Anthropocene epoch.
Subject: 518 Media and communications
113 Computer and information sciences
Social media
Nature conservation
Biodiversity
Spatial analysis
Content analysis
Machine learning
Artificial intelligence
CULTURAL ECOSYSTEM SERVICES
BIG DATA
COMMUNITY DETECTION
NETWORK SITES
TWITTER
CHALLENGES
INTENSITY
PATTERNS
TRADE
SPACE
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