Concerned or Apathetic? Using Social Media Platform (Twitter) to Gauge the Public Awareness about Wildlife Conservation: A Case Study of the Illegal Rhino Trade.
作者: Shan, Siqing; Ju, Xijie; Wei, Yigang; Wen, Xin
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
卷: 19 期: 11
DOI: 10.3390/ijerph19116869
出版时间: 2022-06-03
已索引: 2022-06-11
文献类型: Journal Article; Research Support, Non-U.S. Gov't
摘要:
The illegal wildlife trade is resulting in worldwide biodiversity loss and species' extinction. It should be exposed so that the problems of conservation caused by it can be highlighted and resolutions can be found. Social media is an effective method of information dissemination, providing a real-time, low-cost, and convenient platform for the public to release opinions on wildlife protection. This paper aims to explore the usage of social media in understanding public opinions toward conservation events, and illegal rhino trade is an example. This paper provides a framework for analyzing rhino protection issues by using Twitter. A total of 83,479 useful tweets and 33,336 pieces of users' information were finally restored in our database after filtering out irrelevant tweets. With 2422 records of trade cases, this study builds up a rhino trade network based on social media data. The research shows important findings: (1) Tweeting behaviors are somewhat affected by the information of traditional mass media. (2) In general, countries and regions with strong negative sentiment tend to have high volume of rhino trade cases, but not all. (3) Social celebrities' participation in activities arouses wide public concern, but the influence does not last for more than a month. NGOs, GOs, media, and individual enterprises are dominant in the dissemination of information about rhino trade. This study contributes in the following ways: First, this paper conducts research on public opinions toward wildlife conservation using natural language processing technique. Second, this paper offers advice to governments and conservationist organizations, helping them utilize social media for protecting wildlife.
关键词:
data visualization; rhino trade; sentiment analysis; social media; text mining
地址:
School of Economics and Management, Beihang University, Beijing 100191, China.
Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operation, Beijing 100191, China.
研究方向: Zoology; Computer Science; Sociology
原文下载地址：
https://www.mdpi.com/1660-4601/19/11/6869
