RE-SWOT: From User Feedback to Requirements via Competitor Analysis
1. Does the paper propose a new opinion mining approach?
Yes
2. Which opinion mining techniques are used (list all of them, clearly stating their name/reference)?
The sentiment analysis they perform is very specific for the domain: 𝑆𝑖,𝑗 represents the user sentiment for feature 𝑓𝑗 from app 𝑎𝑖: the sum of the transformed user ratings given to the reviews mentioning the feature, divided by the maximum possible sum. For instance, if a feature is mentioned in two 5-star reviews and one 2-star review, the feature sentiment score for that feature corresponds to (2+2−1)/(2+2+2)=+0.5. (They first normalise stars from 1..5 to -2..2).
3. Which opinion mining approaches in the paper are publicly available? Write down their name and links. If no approach is publicly available, leave it blank or None.
N/A
4. What is the main goal of the whole study?
requirements elicitation from app store reviews through competitor analysis
5. What the researchers want to achieve by applying the technique(s) (e.g., calculate the sentiment polarity of app reviews)?
Understand the way app features are experienced by the users
6. Which dataset(s) the technique is applied on?
Three groups of apps (dating, travel, puzzle games)
7. Is/Are the dataset(s) publicly available online? If yes, please indicate their name and links.
No, commercial
8. Is the application context (dataset or application domain) different from that for which the technique was originally designed?
No
9. Is the performance (precision, recall, run-time, etc.) of the technique verified? If yes, how did they verify it and what are the results?
N/A
10. Does the paper replicate the results of previous work? If yes, leave a summary of the findings (confirm/partially confirms/contradicts).
No
11. What success metrics are used?
N/A
12. Write down any other comments/notes here.
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