Emotion mining and sentiment analysis in software engineering domain

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)?

NLTK, SentiStrength, Watson Natural Language Understanding, Microsoft Text Analytics API

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

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

check the agreement between human evaluators who are familiar with the software engineering terms and sentiment analysis tools

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

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

manually labeled JIRA issue comments

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

JIRA issue comments with labeled sentiment https://www.dropbox.com/sh/l4x6njr4qfy2cos/AABQjl1C7cBnRpSfaFNPyOkFa?dl=0

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

yes, all different

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?

Kappa agreement between approaches. Kappa values obtained between different tools is slightly better compared to manual labelling but still not substantially enough to say that the tools agree with each other.

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.

-