{"title":"基于自然环境的民宿访客评价分析:一种基于NLP的方法","authors":"G. N. Vajpai, D. Pattanaik","doi":"10.53908/nmmr.300201","DOIUrl":null,"url":null,"abstract":"Objective: Sentiment analysis techniques such as Natural Language Processing (NLP) provide a powerful tool to analyze textual data. Along with machine learning and other big data methods, these techniques are used in improving customer service quality in different sectors. This paper utilizes sentiment analysis techniques to identify key themes surrounding visitors’ homestay experience in nature-based settings. Methodology/Approach/Scope: Analysis of 2369 TripAdvisor reviews through Structural Topic Modeling (STM) reveals how high rated homestay experiences differ from those rated low on various parameters. Findings/ Implications/Conclusion – The paper contributes to the knowledge on text mining & its application in improving customer service in the hospitality &tourism domain. The research has practical usage for homestay stakeholders and future direction for further research.","PeriodicalId":43057,"journal":{"name":"NMIMS Management Review","volume":" ","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analyzing Visitors’ Review of Homestays Located in Nature-Based Settings: An NLP Based Approach\",\"authors\":\"G. N. Vajpai, D. Pattanaik\",\"doi\":\"10.53908/nmmr.300201\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objective: Sentiment analysis techniques such as Natural Language Processing (NLP) provide a powerful tool to analyze textual data. Along with machine learning and other big data methods, these techniques are used in improving customer service quality in different sectors. This paper utilizes sentiment analysis techniques to identify key themes surrounding visitors’ homestay experience in nature-based settings. Methodology/Approach/Scope: Analysis of 2369 TripAdvisor reviews through Structural Topic Modeling (STM) reveals how high rated homestay experiences differ from those rated low on various parameters. Findings/ Implications/Conclusion – The paper contributes to the knowledge on text mining & its application in improving customer service in the hospitality &tourism domain. The research has practical usage for homestay stakeholders and future direction for further research.\",\"PeriodicalId\":43057,\"journal\":{\"name\":\"NMIMS Management Review\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.2000,\"publicationDate\":\"2022-04-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NMIMS Management Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.53908/nmmr.300201\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NMIMS Management Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53908/nmmr.300201","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MANAGEMENT","Score":null,"Total":0}
Analyzing Visitors’ Review of Homestays Located in Nature-Based Settings: An NLP Based Approach
Objective: Sentiment analysis techniques such as Natural Language Processing (NLP) provide a powerful tool to analyze textual data. Along with machine learning and other big data methods, these techniques are used in improving customer service quality in different sectors. This paper utilizes sentiment analysis techniques to identify key themes surrounding visitors’ homestay experience in nature-based settings. Methodology/Approach/Scope: Analysis of 2369 TripAdvisor reviews through Structural Topic Modeling (STM) reveals how high rated homestay experiences differ from those rated low on various parameters. Findings/ Implications/Conclusion – The paper contributes to the knowledge on text mining & its application in improving customer service in the hospitality &tourism domain. The research has practical usage for homestay stakeholders and future direction for further research.