Revealing the unrevealed: Mining smartphone users privacy perception on app markets
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)?
VADER Hutto CJ, Gilbert EE. VADER: a parsimonious rule-based model for sentiment analysis of social media text. In: Proceedings of the eighth international conference on weblogs and social media, Ann Arbor, MI, USA; 2014. p. 530–41.
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.
VADER is integrated in NLTK
4. What is the main goal of the whole study?
extract privacy relevant information from app user reviews
5. What the researchers want to achieve by applying the technique(s) (e.g., calculate the sentiment polarity of app reviews)?
determine sentiment of user reviews
6. Which dataset(s) the technique is applied on?
812,899 users reviews associated to the 200 apps within 10 app categories
7. Is/Are the dataset(s) publicly available online? If yes, please indicate their name and links.
It seems not to be available
8. Is the application context (dataset or application domain) different from that for which the technique was originally designed?
Kind of. Reviews
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?
The combined tool reaches the F-score of 93%
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.
Table on p.336 might be an interesting source for another series of papers applying sentiment analysis