Listening to the crowd for the release planning of mobile apps

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)?

Classification of user reviews based on ML

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.

The proposed tool, CLAP, is publicly available: https://dibt.unimol.it/CLAP/

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

To present CLAP, an approach to support developers for the release planning of mobile apps by automatically analyzing its user reviews through a three-step process: categorization of user reviews, clustering of related reviews, and prioritization of review clusters.

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

Provide developers with a quick overview of issues experienced by users of their apps and recommendations they have about features to implement in future.

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

3,000 manually classified user reviews from 705 mobile apps AND The Android user reviews dataset made available by Chen et al. [N. Chen, S. C. Hoi, S. Li, and X. Xiao, “SimApp: A framework for detecting similar mobile applications by online kernel learning,” in Proc. 8th ACM Int. Conf. Web Search Data Mining, 2015, pp. 305–314.]

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

Yes: https://dibt.unimol.it/reports/clap/

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?

Yes. 86% accuracy in categorizing user reviews on the basis of the contained information

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?

Precision, Recall, F-Measure, AUROC

12. Write down any other comments/notes here.

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