Exploration and exploitation of developers' sentimental variations in software engineering

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 with tuning with technical terms

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 study the emotional variations in different types of development activities (e.g., bug-fixing tasks), development periods (i.e., days and times) and in projects of different sizes involving teams of variant sizes.

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 texts

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

top 50 projects from Boa

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

Boa http://boa.cs.iastate.edu/stats/index.php

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

yes but tuned with technical terms

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?

manually verified using a random sample of 200 commit messages extracted from Boa (Dyer, Nguyen, Rajan, & Nguyen, 2013). The manual verification found a 26% increase of precision compared to original SentiStrength.

10. Does the paper replicate the results of previous work? If yes, leave a summary of the findings (confirm/partially confirms/contradicts).

Mp

11. What success metrics are used?

precision

12. Write down any other comments/notes here.

-