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  • 标题:Topic Modeling and Sentiment Analysis of Online Review for Airlines
  • 本地全文:下载
  • 作者:Hye-Jin Kwon ; Hyun-Jeong Ban ; Jae-Kyoon Jun
  • 期刊名称:Information
  • 电子版ISSN:2078-2489
  • 出版年度:2021
  • 卷号:12
  • 期号:2
  • 页码:78
  • DOI:10.3390/info12020078
  • 出版社:MDPI Publishing
  • 摘要:The purpose of this study is to conduct topic modeling and sentiment analysis on the posts of Skytrax (airlinequality.com), where there are many interests and participation of the people who have used or are willing to use it for airlines. The purpose of people gathering at Skytrax is to make better choices using the actual experiences of other customers who have experienced airlines. Online reviews written by customers with experience using airlines in Asia were collected. The data collected were online reviews from 27 airlines, with more than 14,000 reviews. Topic modeling and sentiment analysis were used with the collected data to figure out what kinds of important words are in the online reviews. As a result of the topic modeling, ‘seat’, ‘service’, and ‘meal’ were significant issues in the flight through frequency analysis. Additionally, the result revealed that delay was the main issue, which can affect customer dissatisfaction while ‘staff service’ can make customers satisfied through sentiment analysis as the result shows the ‘staff service’ with meal and food in the topic modeling.
  • 关键词:Asian airlines; online review; sentiment analysis; topic modeling; text mining; big data Asian airlines ; online review ; sentiment analysis ; topic modeling ; text mining ; big data
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