CAPS: a supervised technique for classifying Stack Overflow posts concerning API issues

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, and Senti4SD

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/ Senti4SD: https://github.com/collab-uniba/Senti4SD

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

Summarize expressions about API discussions on SO as feedback to API designers.

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

Assign a sentiment polarity to sentences expressing information about API's on SO.

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

A set of SO posts about three different API's until 5,000 SO posts have been identified, half non-issue, half concerning API issues.

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?

No for Senti4SD, yes for SentiStrength.

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?

Authors indicate that they compared SentiStrength with Senti4SD on their dataset. Sharing that anecdotally Senti4SD is more accurate.

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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