Topic Modeling and Sentiment Analysis using Online Reviews for Bangladesh Airlines

K. M. Hasib, Nurul Akter Towhid, Md. Golam Rabiul Alam
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引用次数: 5

Abstract

Air travel is one of the most used ways of transit in our daily lives. So it's no wonder that more and more people are sharing their experience with airlines and airports using web-based online surveys. This study aims to do topic modeling and sentiment analysis on Skytrax (airlinequality.com) and Tripadvisor (tripadvisor.com) postings where there is a lot of interest and engagement from people who have used it or want to use it for airlines. The goal of individuals gathering at Skytrax and Tripadvisor is to make better decisions based on the actual experiences of other customers who have flown with airlines. We gathered online reviews submitted by consumers who have flown with Bangladesh airlines in the past. The data was collected from internet reviews from 4 Bangladesh airlines, totaling 1095 reviews. With the obtained data, topic modeling and sentiment analysis were utilized to determine key phrases in the online reviews. Through frequency analysis, the topic modeling revealed that ‘airline,’ ‘service,’ ‘crew,’ and ‘food’ were essential concerns in the trip. Furthermore, the results indicated that the primary issue, which may impact customer discontent, was delay, but ‘food’ can make customers satisfied through sentiment analysis, as the result indicates the ‘Food and beverage’ topic with no. of highest word count ‘good’, ‘biman’ and ‘service’ keyword in the topic modeling.
基于孟加拉航空在线评论的主题建模和情感分析
航空旅行是我们日常生活中最常用的交通方式之一。因此,越来越多的人通过网络在线调查与航空公司和机场分享他们的经历也就不足为奇了。这项研究的目的是对Skytrax (airlinequality.com)和Tripadvisor (tripadvisor.com)的帖子进行主题建模和情感分析,因为这些帖子中有很多已经使用或想要使用Skytrax的人对航空公司的帖子感兴趣并参与其中。人们聚集在Skytrax和Tripadvisor上的目的是,根据其他乘坐过航空公司航班的客户的实际体验,做出更好的决策。我们收集了过去乘坐过孟加拉国航空公司航班的消费者提交的在线评论。数据收集自4家孟加拉国航空公司的互联网评论,共计1095条评论。利用获得的数据,利用主题建模和情感分析来确定在线评论中的关键短语。通过频率分析,主题建模显示“航空公司”、“服务”、“机组人员”和“食物”是旅行中最重要的关注点。此外,结果表明,可能影响顾客不满的主要问题是延迟,但“食品”可以通过情绪分析使顾客满意,因为结果表明“食品和饮料”话题没有。在主题建模中字数最高的关键词是“good”、“bman”和“service”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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