# Improving RE-SWOT Analysis with Sentiment Classification: A Case Study of Travel Agencies
## 2 Related Works
### SWOT Development Based on User Reviews  
[PERSON] and [PERSON] [10] proposed a method for requirements engineering based on SWOT analysis. Requirements engineering refers to the application of effective technologies to help companies understand and determine customer requirements. [PERSON] and [PERSON] believe that user comments are an important basis for understanding customer requirements, so they designed a process to extract product features mentioned by users and the user ratings about the products. The final output of the process is the SWOT matrix, and requirements engineering is based on this matrix. Here, we briefly describe [PERSON] and [PERSON]'s SWOT matrix before moving onto a closer examination of the process. [PERSON] and [PERSON] called the matrix built by this process the RE-SWOT matrix, as illustrated by Figure 2.  
Features are strengths of a company's own product if the performance of this product has a positive or above average evaluation compared with competing products. Similarly, weaknesses are features of a product that perform negatively or below average when compared with competing products. Threats are features of competing products that perform positively or above the market average, and opportunities come from the features of the competitor that perform negatively or below the market average. Having described the RE-SWOT matrix, we now explain the steps taken to generate the RE-SWOT matrix:  
Step 1: Identify features and transform ratings. First, the user reviews and ratings on the target product and its competing products are retrieved. Then, those user reviews are preprocessed using the Natural Language Processing (NLP) technique to identify the mentioned features. The original 5-point rating is transformed into a number on a scale from \(-2\) to \(2\). Figure 1: SWOT matrix. Figure 2: RE-SWOT matrix. Step 2: Calculate the FPS per feature. For a feature \(j\) of a product \(i\), the feature performance score (FPS) is calculated as shown in Equation (1). \[FPS_{i,j}=\frac{S_{i,j}\cdot V_{i,j}}{\sum_{i=1}^{m}\left|S_{i,j}V_{i,j}\right|}, \text{ and }s_{i,j}=\frac{\sum_{k=1}^{V_{i,j}}r_{ij}[k]}{2\times V_{i,j}}. \tag{1}\]  
In Equation (1), \(m\) is the number of products, \(V_{i,j}\) is the number of reviews mentioning feature \(j\) related to product \(i\), and \(r_{ij}[k]\) is the transformed rating of the \(k\)-th user review mentioning feature \(j\) of product \(i\), and \(k=1..V_{i,j}\). Step 3: Classify each feature. According to the FPS score, each feature is classified as positive or negative and above the market average or below the market average. A feature \(j\) is considered a positive element of product \(i\) if \(FPS_{i,j}\geq\sigma\) or negative if \(FPS_{i,j}\leq-\sigma\). The performance of feature \(j\) of product \(i\) is above the market average if \(FPS_{i,j}-\overline{FPS_{i,j}}\geq~{}\sigma\) or below market average if \(FPS_{i,j}-\overline{FPS_{i,j}}\leq-\sigma\). In addition, a feature is considered unique if its FPS score is 1 or \(-1\). In the experiment, [PERSON] and [PERSON] set \(\sigma=0.1\). Step 4: Generate the RE-SWOT matrix. The positive and above market average features of a company's own product can be considered strengths, and those that are negative or below the market average can be considered weaknesses. On the contrary, positive and above market average features of competing products can be considered threats to the company's own product, and negative and below market average features of competing products can be considered opportunities for the company's own product. In [PERSON] and [PERSON]'s study, the products were mobile apps, so the user reviews and ratings were retrieved from the app store. User reviews and ratings are obtained from different platforms for different products. In principle, credible platforms should be used and the product's official website should be avoided. The app store is a third-party platform for mobile apps and does not belong to any app company, so the reviews and ratings on it can be regarded as objective.