Sammanfattning

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.
Originalspråkengelska
TidskriftBiological Conservation
Volym233
Sidor (från-till)298-315
Antal sidor18
ISSN0006-3207
DOI
StatusPublicerad - maj 2019
MoE-publikationstypA2 Granska artikel i en vetenskaplig tidskrift

Vetenskapsgrenar

  • 518 Medie- och kommunikationsvetenskap
  • 113 Data- och informationsvetenskap

Citera det här

@article{7e1f9b012934422faed8a5a93fa50e49,
title = "Social media data for conservation science: A methodological overview",
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.",
keywords = "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",
author = "Tuuli Toivonen and Vuokko Heikinheimo and Christoph Fink and Anna Hausmann and Tuomo Hiippala and Olle J{\"a}rv and Henrikki Tenkanen and {Di Minin}, Enrico",
year = "2019",
month = "5",
doi = "10.1016/j.biocon.2019.01.023",
language = "English",
volume = "233",
pages = "298--315",
journal = "Biological Conservation",
issn = "0006-3207",
publisher = "ELSEVIER SCI IRELAND LTD",

}

TY - JOUR

T1 - Social media data for conservation science

T2 - A methodological overview

AU - Toivonen, Tuuli

AU - Heikinheimo, Vuokko

AU - Fink, Christoph

AU - Hausmann, Anna

AU - Hiippala, Tuomo

AU - Järv, Olle

AU - Tenkanen, Henrikki

AU - Di Minin, Enrico

PY - 2019/5

Y1 - 2019/5

N2 - 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.

AB - 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.

KW - 518 Media and communications

KW - 113 Computer and information sciences

KW - Social media

KW - Nature conservation

KW - Biodiversity

KW - Spatial analysis

KW - Content analysis

KW - Machine learning

KW - Artificial intelligence

KW - CULTURAL ECOSYSTEM SERVICES

KW - BIG DATA

KW - COMMUNITY DETECTION

KW - NETWORK SITES

KW - TWITTER

KW - CHALLENGES

KW - INTENSITY

KW - PATTERNS

KW - TRADE

KW - SPACE

U2 - 10.1016/j.biocon.2019.01.023

DO - 10.1016/j.biocon.2019.01.023

M3 - Review Article

VL - 233

SP - 298

EP - 315

JO - Biological Conservation

JF - Biological Conservation

SN - 0006-3207

ER -