# Improving RE-SWOT Analysis with Sentiment Classification: A Case Study of Travel Agencies  
[PERSON]  
1 Department of Information Management, Chinese Culture University, Taipei 11114, Taiwan;  
1 [EMAIL_ADDRESS] Department of Information Management, Ming Chuan University, Taoyuan 33300, Taiwan;  
1 [EMAIL_ADDRESS]  
[PERSON]  
2 Department of Information Management, Ming Chuan University, Taoyuan 33300, Taiwan;  
2 [EMAIL_ADDRESS]  
[PERSON]  
2 School of Natural Science, University of  
a long time ago. Some researchers consider the origin of SWOT to be obscure, but [PERSON] et al. [4] believes that SWOT originated in the early 1950s. Though SWOT analysis is an ancient method, it is still a widely used strategic planning tool [5; 6; 7; 8; 9]. In 2019, [PERSON] and [PERSON] proposed a tool, known as RE-SWOT, which utilizes user reviews to generate a SWOT matrix, which is then used for the elicitation of requirements [10]. [PERSON] and [PERSON] retrieved the user reviews and ratings of the target product to identify strengths and weaknesses. Opportunities and threats were determined from the user reviews and ratings of the competitive products. [PERSON] and [PERSON] took the app as the research object to illustrate how to use the proposed method to generate the SWOT matrix. [PERSON] and [PERSON]'s study is very useful because it provides a way to automatically generate a SWOT matrix based on users' comments. This study intends to investigate how to utilize [PERSON] and [PERSON]'s method to build the SWOT matrix for KKday products. The user reviews and ratings needed to generate the SWOT matrix are available on the KKday website, but they may be less objective because the company has the authority to delete or retain the comments. User reviews and ratings are preferably obtained from third-party websites, such as the TripAdvisor forum. TripAdvisor is the largest travel forum, having users all over the world, and it has become the main source of data for many travel-related studies, because its online reviews are less likely to be changed by the owners of the tourist company [11]. However, the TripAdvisor forum lacks user ratings, which are required for [PERSON] and [PERSON]'s method to create a SWOT matrix. If the problem of a lack of user ratings can be solved, [PERSON] and [PERSON]'s method could be widely applied in various scenarios. Recently, some companies have tried to extract comments on their own products from the web and use a sentiment analysis to analyze the polarity or general feeling of the comments [12]. Sentiment analysis, also known as sentiment classification or opinion mining, refers to the use of natural language processing (NLP), text analysis, and computer linguistics to systematically identify, extract, and quantify the subjectivity of the text [13]. The application of sentiment analysis to the tourism industry has previously been proposed [14; 15; 16; 17; 18; 19]. Polarity means the quantified value of the sentiment, and its classification can be binary (positive or negative), triple (positive, negative, or neutral), or more. Therefore, sentiment analysis provides a possible solution to the problem that the [PERSON] and [PERSON]'s method will not work if user ratings are missing. We can use sentiment analysis to determine the polarity of the sentiment in user reviews and then use the polarity to represent the user rating. In summary, [PERSON] and [PERSON]'s method is a good way to automatically generate a SWOT matrix, which is an important tool for competitive analysis. This study applied [PERSON] and [PERSON]'s method to create a SWOT matrix for an OTA, using KKday as an example. The user reviews were collected from the TripAdvisor forum, and the user ratings, which are required by [PERSON] and [PERSON]'s method but are not available in the TripAdvisor forum, were replaced by the polarity of sentiment in the reviews. In this way, we made [PERSON] and [PERSON]'s method applicable to the OTA.