Online sentiment towards iconic species

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Fink , C , Hausmann , A & Di Minin , E 2020 , ' Online sentiment towards iconic species ' , Biological Conservation , vol. 241 , 108289 . https://doi.org/10.1016/j.biocon.2019.108289

Title: Online sentiment towards iconic species
Author: Fink, Christoph; Hausmann, Anna; Di Minin, Enrico
Contributor: University of Helsinki, Helsinki Lab of Interdisciplinary Conservation Science
University of Helsinki, Helsinki Lab of Interdisciplinary Conservation Science
University of Helsinki, Department of Geosciences and Geography
Date: 2020-01
Language: eng
Number of pages: 8
Belongs to series: Biological Conservation
ISSN: 0006-3207
URI: http://hdl.handle.net/10138/312301
Abstract: Studies assessing online public sentiment towards biodiversity conservation are almost non-existent. The use of social media data and other online data sources is increasing in conservation science. We collected social media and online news data pertaining to rhinoceros, which are iconic species especially threatened by illegal wildlife trade, and assessed online sentiment towards these species using natural language processing methods. We also used an outlier detection technique to identify the most prominent conservation-related events imprinted into this data. We found that tragic events, such as the death of the last male northern white rhinoceros, Sudan, in March 2018, triggered the strongest reactions, which appeared to be concentrated in western countries, outside rhinoceros range states. We also found a strong temporal cross-correlation between social media data volume and online news volume in relation to tragic events, while other events only appeared in either social media or online news. Our results highlight that the public is concerned about biodiversity loss and this, in turn, can be used to increase pressure on decision makers to develop adequate conservation actions that can help reverse the biodiversity crisis. The proposed methods and analyses can be used to infer sentiment towards any biodiversity topic from digital media data, and to detect which events are perceived most important to the public.
Subject: 1171 Geosciences
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