A Feature-Oriented Sentiment Rating for Mobile App Reviews
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)?
Saci: Sentiment analysis by collective inspection on social media content - this is not really a tool but more of an approach.
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.
Saci is publicly available
4. What is the main goal of the whole study?
To provide a more fine-grained rating of mobile apps
5. What the researchers want to achieve by applying the technique(s) (e.g., calculate the sentiment polarity of app reviews)?
To support app developers via a summarization interface including visualisation of the features (i.e., topics) and their associated sentiment
6. Which dataset(s) the technique is applied on?
Seven collections of user reviews followed by their star ratings extracted from Google Play Store collected by Guzman and Maalej in How do users like this feature? a fine grained sentiment analysis of app reviews.
7. Is/Are the dataset(s) publicly available online? If yes, please indicate their name and links.
https://mast.informatik.uni-hamburg.de/app-review-analysis/ -> How do users like this feature?
8. Is the application context (dataset or application domain) different from that for which the technique was originally designed?
N/A
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?
Comparison of the sentiment analysis results with the star rating of the apps
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.
This paper and it seems that many others in my batch are not related to communication between developers.