On the Emotion of Users in App Reviews
1. Does the paper propose a new opinion mining approach?
No
2. Which opinion mining techniques are used (list all of them, clearly stating their name/reference)?
SentiStrength extended to support emojis
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.
SentiStrength, not the extended version
4. What is the main goal of the whole study?
To analyze over seven million reviews from the Apple AppStore regarding their emotional sentiment
5. What the researchers want to achieve by applying the technique(s) (e.g., calculate the sentiment polarity of app reviews)?
SentiStrength: to calculate the sentiment in the reviews
6. Which dataset(s) the technique is applied on?
app reviews for five free and paid apps (by December 18, 2016) for each of the 25 categories of the Apple AppStore.
7. Is/Are the dataset(s) publicly available online? If yes, please indicate their name and links.
App Reviews: available upon request on https://mast.informatik.uni-hamburg.de/app-review-analysis/
8. Is the application context (dataset or application domain) different from that for which the technique was originally designed?
Yes
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?
No
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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