An empirical study of sentiments in code 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)?

Senti4SD | http://refhub.elsevier.com/S0950-5849(19)30138-7/sbref0011 SentiCR | http://refhub.elsevier.com/S0950-5849(19)30138-7/sbref0012 Sentistrength_SE | http://refhub.elsevier.com/S0950-5849(19)30138-7/sbref0013

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.

All of them, see above

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

Compare the three approaches in terms of sentiment analysis in code reviews

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

Compare the approaches

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

Dataset of code reviews, publicly available: http://refhub.elsevier.com/S0950-5849(19)30138-7/sbref0039

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

Yes, http://refhub.elsevier.com/S0950-5849(19)30138-7/sbref0039

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?

Mann–Whitney U test for the comparison

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?

None

12. Write down any other comments/notes here.

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