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LI Xiao-kun

Biographic Data

ID6645923
NAMELI Xiao-kun
GIVEN NAMESLI
FAMILY NAMEXiao-kun
SIGNATUREXIAO-KUN L
AFFILIATIONSNortheastern University
ORCID0000-0001-5230-5576
VERIFIEDYes
TOTAL WORKS1
TOTAL CITATIONS2
AUTHOR COUNT1
EDITOR COUNT0
FIRST PUBLICATION YEAR2023
LATEST PUBLICATION YEAR2023
H-INDEX1
  • Analyzing online reviews of foreign tourists to destination attractions in China

    LI Xiao-kun, Yao Zhang et al.•ARTICLE•Asia Pacific Journal of Tourism…•2023•Cited by: 2•References: 6

    In recent years, China has been gradually improving its tourism services along with its economic development. Inbound tourism not only boosts the economy of China, but also creates issues and challenges for tourism administration. The purpose of this study is to develop a novel text mining approach that combines topic modeling and sentiment analysis for exploring the dynamic evolution of topic intensity of destination attractions and discovering …

  • Analyzing online reviews of foreign tourists to destination attractions in China

    LI Xiao-kun, Yao Zhang et al.•ARTICLE•Asia Pacific Journal of Tourism…•2023•Cited by: 2•References: 6

    In recent years, China has been gradually improving its tourism services along with its economic development. Inbound tourism not only boosts the economy of China, but also creates issues and challenges for tourism administration. The purpose of this study is to develop a novel text mining approach that combines topic modeling and sentiment analysis for exploring the dynamic evolution of topic intensity of destination attractions and discovering …

  • Analyzing online reviews of foreign tourists to destination attractions in China

    LI Xiao-kun, Yao Zhang et al.•ARTICLE•Asia Pacific Journal of Tourism…•2023•Cited by: 2•References: 6

    In recent years, China has been gradually improving its tourism services along with its economic development. Inbound tourism not only boosts the economy of China, but also creates issues and challenges for tourism administration. The purpose of this study is to develop a novel text mining approach that combines topic modeling and sentiment analysis for exploring the dynamic evolution of topic intensity of destination attractions and discovering …

Advertising (1 work) · Business (1 work) · China (1 work) · Computer Science (1 work) · Digital Marketing and Social Media (1 work) · Diverse Aspects of Tourism Research (1 work) · Geography (1 work) · Information retrieval (1 work) · Latent Dirichlet allocation (1 work) · Marketing (1 work)

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