Developers' Sentiment and Issue Reopening

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)?

SentiStrengthSE

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.

SentiStrengthSE

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

Understand the sentiment in relation to issue reopening.

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

RQ1: Are comments with negative sentiments more likely to appear in issues that have been reopened? RQ2: Does a larger comment size correlate with more extreme sentiment scores? RQ3: Do different projects have different proportions in regards to sentiment scores and issue reopening status?

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

Ad hoc dataset of 3000 issues stemming from an ad hoc set 8 software systems

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

No, although there is a link, but it is dead

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?

It is verified, but only using percentages of issues with no, 1, or more reopenings

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?

Ad hoc score system

12. Write down any other comments/notes here.

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