Stratify Mobile App Reviews: E-LDA Model Based on Hot" Entity" Discovery
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)?
SAR (Stratify App Reviews) E-LDA Topic Model: based on LDA Mixed Sentiment Computing: an algorithm based sentistrength
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.
None
4. What is the main goal of the whole study?
to provide developers information about users’ real reaction toward apps.
5. What the researchers want to achieve by applying the technique(s) (e.g., calculate the sentiment polarity of app reviews)?
E-LDA: finding out those entities that mostly reviewed by users Mixed Sentiment Computing: calculating user sentiment on app entities
6. Which dataset(s) the technique is applied on?
reviews and ratings of 6 apps from google play (Virtual Table Tennis, Bubble Shooter, Quora, Tumblr, YouTube, Speaker Boost)
7. Is/Are the dataset(s) publicly available online? If yes, please indicate their name and links.
No
8. Is the application context (dataset or application domain) different from that for which the technique was originally designed?
No
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?
E-LDA tested
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?
Perplexity result, recall, precision, and F-measure
12. Write down any other comments/notes here.
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