The role of emotions in contributors activity: A case study on the gentoo community

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

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

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

To analyze the relation between the emotions and the activity of contributors in an Open Source Software project (GENTOO). They found that contributors are more likely to become inactive when they express strong positive or negative emotions in the bug tracker.

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

Calculate the sentiment polarity of messages in issue tracker and mailing list

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

Issue tracker (~660k messages) and mailing list (81k messages) of the studied project.

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

No

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

Yes, SentiStrength is not customized

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?

None

12. Write down any other comments/notes here.

-