{"title":"分析外国游客对中国旅游景点的在线评论:一种新颖的文本挖掘方法","authors":"Xiaokun Li, Yao Zhang, Liyang Mei","doi":"10.1080/10941665.2023.2255315","DOIUrl":null,"url":null,"abstract":"ABSTRACT 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 the reasons for foreign tourists’ dissatisfactions. To this end, we propose an LDA-based topic evolution model, develop a tourism-oriented VADER dictionary and introduce an integration method for screening negative reviews. Then, the approach was used to analyze 80,546 online travel reviews from foreign tourists on TripAdvisor for 10 popular destination attractions in China from 2011 to 2019. The findings can help tourism practitioners better understand the changes and trends of the topics over time as well as develop strategies with respect to tourists’ dissatisfactions.","PeriodicalId":47998,"journal":{"name":"Asia Pacific Journal of Tourism Research","volume":"19 1","pages":"647 - 666"},"PeriodicalIF":4.3000,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analyzing online reviews of foreign tourists to destination attractions in China: a novel text mining approach\",\"authors\":\"Xiaokun Li, Yao Zhang, Liyang Mei\",\"doi\":\"10.1080/10941665.2023.2255315\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT 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 the reasons for foreign tourists’ dissatisfactions. To this end, we propose an LDA-based topic evolution model, develop a tourism-oriented VADER dictionary and introduce an integration method for screening negative reviews. Then, the approach was used to analyze 80,546 online travel reviews from foreign tourists on TripAdvisor for 10 popular destination attractions in China from 2011 to 2019. The findings can help tourism practitioners better understand the changes and trends of the topics over time as well as develop strategies with respect to tourists’ dissatisfactions.\",\"PeriodicalId\":47998,\"journal\":{\"name\":\"Asia Pacific Journal of Tourism Research\",\"volume\":\"19 1\",\"pages\":\"647 - 666\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2023-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asia Pacific Journal of Tourism Research\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1080/10941665.2023.2255315\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HOSPITALITY, LEISURE, SPORT & TOURISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asia Pacific Journal of Tourism Research","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1080/10941665.2023.2255315","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HOSPITALITY, LEISURE, SPORT & TOURISM","Score":null,"Total":0}
Analyzing online reviews of foreign tourists to destination attractions in China: a novel text mining approach
ABSTRACT 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 the reasons for foreign tourists’ dissatisfactions. To this end, we propose an LDA-based topic evolution model, develop a tourism-oriented VADER dictionary and introduce an integration method for screening negative reviews. Then, the approach was used to analyze 80,546 online travel reviews from foreign tourists on TripAdvisor for 10 popular destination attractions in China from 2011 to 2019. The findings can help tourism practitioners better understand the changes and trends of the topics over time as well as develop strategies with respect to tourists’ dissatisfactions.
期刊介绍:
Asia Pacific Journal of Tourism Research is the official journal of the Asia Pacific Tourism Association (Founded September 1995) and seeks to publish both empirically and theoretically based articles which advance and foster knowledge of tourism as it relates to the Asia Pacific region. The Journal welcomes submissions of full length articles and critical reviews on major issues with relevance to tourism in the Asia Pacific region.