Fave: Visualizing user feedback for software evolution

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, LDA

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.

all

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

to present an interactive user feedback visualization

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

NLTK: to extract features from the user reviews with collocation finding algorithm SentiStrength: to calculate the sentiment polarity of reviews LDA: to group features that tend to co-occur in the same reviews

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

app reviews from E. Guzman and W. Maalej. Do Users Like this Feature? A Fine Grained Sentiment Analysis of App Reviews. In Proc. of the International Conference on Requirements Engineering

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

app review data https://mast.informatik.uni-hamburg.de/app-review-analysis/

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?

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.

Just a tool for visualization