On the Use of Emoticons in Open Source Software Development
1. Does the paper propose a new opinion mining approach?
Yes
2. Which opinion mining techniques are used (list all of them, clearly stating their name/reference)?
It is not really an opinion mining technique. The technique does not have a name; the authors detect emoticons in Apache/Mozilla issue comments and a manual mapping of emoticons to emotions.
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.
The Emoticons/Emotions manual mapping https://github.com/M3SOulu/ESEM2018-Emoticons-Emotions-List including regular expressions to identify emoticons https://github.com/M3SOulu/ESEM2018-Emoticons-Emotions-List/blob/master/emoticons_regex.csv
4. What is the main goal of the whole study?
(1) to understand how software developers use emoticons differently in issue trackers of different ecosystems. (2) to which extent emoticons can be used as in place of sentiment analysis.
5. What the researchers want to achieve by applying the technique(s) (e.g., calculate the sentiment polarity of app reviews)?
As above
6. Which dataset(s) the technique is applied on?
1.3M Apache comments and 4.5M Mozilla comments
7. Is/Are the dataset(s) publicly available online? If yes, please indicate their name and links.
The dataset is not made public
8. Is the application context (dataset or application domain) different from that for which the technique was originally designed?
N/A new technique
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, the technique is presumed to be correct by design
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.
GitHub M3SOulu also has a different tool for detection of emoticons in textual data https://github.com/M3SOulu/EmoticonFindeR