ダハラン ナリマン   DAHLAN Nariman    所属   立命館アジア太平洋大学  サステイナビリティ観光学部    職種   准教授
言語種別	英語
発行・発表の年月	2024/11/12
形態種別	著書（チャプター）
査読	査読あり
標題	Sentiment Analysis of Hotel Reviews Using Lexicon-Based Methods: A Comparative Study of VADER and TextBlob
執筆形態	単著
掲載誌名	Lecture Notes on Data Engineering and Communications Technologies
掲載区分	国外
出版社・発行元	Springer, Cham
巻・号・頁	231,pp.263-274
総ページ数	12
概要	The main purpose of this study is to explore the potential of utilizing Social Big Data and text mining techniques to benefit stakeholders in the tourism and hospitality industry. We examine the impact of lexicon-based sentiment analysis approaches using VADER and TextBlob. Additionally, we investigate the performance of these tools across different hotel customer reviews. Preliminary results indicate that VADER demonstrates more consistent and reliable performance across different thresholds. It maintains high precision, recall, and accuracy, making it a more stable model for sentiment analysis. While TextBlob performs well at lower thresholds, its performance deteriorates at higher thresholds, particularly in terms of recall and accuracy. In conclusion, the VADER and TextBlob features discovered in this study provide valuable insights for sentiment analysis practitioners in the hospitality industry.
researchmap用URL	https://doi.org/10.1007/978-3-031-76452-3_25