Utilizing Text Mining to Identify Trends and Patterns within the Contextof Smart Hotels and Hotel Internet of Things (IoT)
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As technology becomes integral to customer experiences, the study investigates the adoption of technologies in hotels and their influence on traditional service. The integration of IoT is explored for its potential to create new experiences and increase customer satisfaction, alongside challenges such as security concerns and high investment costs. Therefore, this research gathered Google News data using the keywords "Smart Hotel" and "Hotel IoT" to analyze emerging trends in the hospitality sector. Co-occurrence network analysis and Latent Dirichlet Allocation (LDA) topic modeling unveil key clusters and topics, emphasizing customer experience, technology amenities, and intelligent operation. The findings contribute valuable insights into the evolving landscape of smart hotels and the relationship between IoT and the hospitality sector.
Abstract
As technology becomes integral to customer experiences, the study investigates the adoption of technologies in hotels and their influence on traditional service. The integration of IoT is explored for its potential to create new experiences and increase customer satisfaction, alongside challenges such as security concerns and high investment costs. Therefore, this research gathered Google News data using the keywords "Smart Hotel" and "Hotel IoT" to analyze emerging trends in the hospitality sector. Co-occurrence network analysis and Latent Dirichlet Allocation (LDA) topic modeling unveil key clusters and topics, emphasizing customer experience, technology amenities, and intelligent operation. The findings contribute valuable insights into the evolving landscape of smart hotels and the relationship between IoT and the hospitality sector.
참고문헌 (36)
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