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What can the news tell us about the environmental performance of tourist areas? A text mining approach to China’s National 5A Tourist Areas
چه خبرهایی می تواند از عملکرد زیست محیطی مناطق توریستی به ما بگوید؟ یک رویکرد استخراج متن به مناطق گردشگری ملی 5A در چین-2020 This study aims to evaluate the environmental performance status of tourist areas and explore the influencing
factors using text mining of web news. As the leading tourist attractions in China, the National 5A Tourist Areas
face severe environmental challenges, and were hence chosen to exemplify the rapid assessment approach in the
big data era. This study used over 1,300,000 words from online news sources and assessed the environmental
performance of 120 National 5A Tourist Areas to conclude that (1) water is the most impacted environmental
resource; (2) tourist area environmental performance can be classified into (a) environmental pollution, (b)
ecological and resource pressure, (c) landscape character issues and (d) others; and (3) the primary factors
influencing the environment are tourism and business operating activities, with the tourist areas’ environmental
performance types being strongly related to their spatial locations and weakly related to their resource types. By
comparing the environmental performance types in this paper with related research the effectiveness of this
study’s approach is validated. These conclusions and this approach can provide guidelines and tools for environmental
assessment and promote tourist area management Keywords: Environmental impact assessment | Environmental pollution | Tourist environment | Web content | Text mining | China’s National 5A Tourist Areas |
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