Sentiment analysis and classification for software as a service reviews

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)?

Semantria, by Lexalytics https://www.lexalytics.com/semantria and https://www.lexalytics.com/technology/sentiment-analysis

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.

Semantria is a commercial tool

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

classification for Software as a Service Reviews

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

calculate sentiment polarity of SaaS reviews

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

4000 reviews

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

http://www.bluepagesdataset.com/ but the website is offline

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

Lexalytics discusses their tool in context of user feedback and communication between employees. Presumably SaaS reviews were not on their mind.

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

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.

N/A