The challenges of sentiment detection in the social programmer ecosystem

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 http://sentistrength.wlv.ac.uk/

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/

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

Understand why is it difficult to detect sentiment expressed by software developers

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

Calculate sentiment of SO questions, answers and comments

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

We analyzed the top 100 questions and follow-up askers’ comments with the highest positive and negative scores (400 cases overall). Analogously, we analyzed the 100 top answers and follow-up answerers’ comments with the highest positive and negatives score (400 additional cases).

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

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?

Yes. Essentially the entire paper is discussion of misclassifications

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.

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