How angry are your customers? Sentiment analysis of support tickets that escalate
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 NLU
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.
NLTK https://text-processing.com/demo/sentiment/ SentiStrength http://sentistrength.wlv.ac.uk/ Watson NLU https://www.ibm.com/cloud/watson-natural-language-understanding They seem to have a free version (limited in time? functionality?)
4. What is the main goal of the whole study?
Is the sentiment in an escalated support ticket significantly different than the sentiment in a non-escalated support ticket?
5. What the researchers want to achieve by applying the technique(s) (e.g., calculate the sentiment polarity of app reviews)?
compute sentiment of support tickets
6. Which dataset(s) the technique is applied on?
10172 emails in 655 support tickets
7. Is/Are the dataset(s) publicly available online? If yes, please indicate their name and links.
Data is not available (IBM)
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?
It is not verified against some kind of ground truth; the tools are compared 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).
Not explicitly
11. What success metrics are used?
N/A
12. Write down any other comments/notes here.
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