作者:Fu, Y (Fu, Yu)[ 1 ] ; Hao, JX (Hao, Jin-Xing)[ 1 ] ; Li, X (Li, Xiang (Robert))[ 2 ] ; Hsu, CHC (Hsu, Cathy H. C.)[ 3 ]
JOURNAL OF TRAVEL RESEARCH
卷: 58期: 4
页: 666-679
DOI: 10.1177/0047287518772361
出版年: APR 2019
文献类型:Article
摘要
Sentiment analytics, as a computational method to extract emotion and detect polarity, has gained increasing attention in tourism research. However, issues regarding how to properly apply sentiment analytics are seldom addressed in the tourism literature. This study addresses such methodological challenges by employing the metalearning perspective to examine the design effects on predictive accuracy using a sentiment analysis experiment for Chinese travel news. Our results reveal strong interactions among key design factors of sentiment analytics on predictive accuracy; accordingly, this study formulates a metalearning framework to improve predictive accuracy for computational tourism research. Our study attempts to highlight and improve the methodological relevance and appropriateness of sentiment analytics for future tourism studies.
关键词
作者关键词:sentiment analytics; design effects; predictive accuracy; metalearning; Chinese travel news
KeyWords Plus:SUPPORT VECTOR MACHINES; QUALITY-OF-LIFE; ONLINE REVIEWS; SOCIAL-SCIENCE; MEDIA; CLASSIFICATION; HOSPITALITY; PERCEPTIONS; INDUSTRY; IMPACT
作者信息
通讯作者地址:
Beihang University Beihang Univ, Sch Econ & Management, 37 Xueyuan Rd, Beijing 100191, Peoples R China.
通讯作者地址: Hao, JX (通讯作者)
Beihang Univ, Sch Econ & Management, 37 Xueyuan Rd, Beijing 100191, Peoples R China.
地址:
[ 1 ]Beihang Univ, Sch Econ & Management, 37 Xueyuan Rd, Beijing 100191, Peoples R China
[ 2 ]Temple Univ, Dept Tourism & Hospitality Management, Philadelphia, PA 19122 USA
[ 3 ]Hong Kong Polytech Univ, Sch Hotel & Tourism Management, TST East, Kowloon, Hong Kong, Peoples R China
电子邮件地址:hao@buaa.edu.cn
https://journals.sagepub.com/doi/10.1177/0047287518772361
