How do users like this feature? a fine grained sentiment analysis of 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 http://sentistrength.wlv.ac.uk/

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 http://sentistrength.wlv.ac.uk/

4. What is the main goal of the whole study?

Feature based sentiment analysis of app reviews

5. What the researchers want to achieve by applying the technique(s) (e.g., calculate the sentiment polarity of app reviews)?

compute sentiment of review fragments

6. Which dataset(s) the technique is applied on?

2928 features

7. Is/Are the dataset(s) publicly available online? If yes, please indicate their name and links.

https://mast.informatik.uni-hamburg.de/app-review-analysis/ - How Do Users Like this Feature?

8. Is the application context (dataset or application domain) different from that for which the technique was originally designed?

Kind of, again reviews but not app reviews per se.

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?

Yes. The Spearman’s rho correlation coefficient between the sentence-based sentiment score and the truth set was of 0.445 (p-value< 2.2e-16), indicating a moderate positive correlation between them.

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.

-