Abstract
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.
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