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--- |
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annotations_creators: |
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- crowdsourced |
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language_creators: |
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- crowdsourced |
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language: |
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- en |
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license: |
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- unknown |
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multilinguality: |
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- monolingual |
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size_categories: |
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- 100K<n<1M |
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source_datasets: |
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- original |
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task_categories: |
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- text-classification |
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task_ids: |
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- text-scoring |
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- sentiment-scoring |
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paperswithcode_id: null |
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pretty_name: AppReviews |
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dataset_info: |
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features: |
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- name: package_name |
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dtype: string |
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- name: review |
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dtype: string |
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- name: date |
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dtype: string |
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- name: star |
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dtype: int8 |
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splits: |
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- name: train |
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num_bytes: 32769079 |
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num_examples: 288065 |
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download_size: 42592679 |
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dataset_size: 32769079 |
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--- |
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# Dataset Card for [Dataset Name] |
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## Table of Contents |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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## Dataset Description |
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- **Homepage:** [Home Page](https://github.com/sealuzh/user_quality) |
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- **Repository:** [Repo Link](https://github.com/sealuzh/user_quality) |
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- **Paper:** [Link](https://giograno.me/assets/pdf/workshop/wama17.pdf) |
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- **Leaderboard: |
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- **Point of Contact:** [Darshan Gandhi]([email protected]) |
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### Dataset Summary |
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It is a large dataset of Android applications belonging to 23 different app categories, which provides an overview of the types of feedback users report on the apps and documents the evolution of the related code metrics. The dataset contains about 395 applications of the F-Droid repository, including around 600 versions, 280,000 user reviews (extracted with specific text mining approaches) |
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### Supported Tasks and Leaderboards |
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The dataset we provide comprises 395 different apps from the F-Droid repository, including code quality indicators of 629 versions of these |
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apps. It also encloses app reviews related to each of these versions, which have been automatically categorized classifying types of user feedback from a software maintenance and evolution perspective. |
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### Languages |
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The dataset is a monolingual dataset that has the messages in English. |
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## Dataset Structure |
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### Data Instances |
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The dataset consists of a message in English. |
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{'package_name': 'com.mantz_it.rfanalyzer', |
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'review': "Great app! The new version now works on my Bravia Android TV which is great as it's right by my rooftop aerial cable. The scan feature would be useful...any ETA on when this will be available? Also the option to import a list of bookmarks e.g. from a simple properties file would be useful.", |
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'date': 'October 12 2016', |
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'star': 4} |
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### Data Fields |
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* package_name: Name of the Software Application Package |
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* Review : Message of the user |
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* date: the date when the user posted the review |
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* star: rating provided by the user for the application |
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### Data Splits |
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There is training data, with a total of 288065 |
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## Dataset Creation |
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### Curation Rationale |
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[More Information Needed] |
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### Source Data |
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#### Initial Data Collection and Normalization |
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[More Information Needed] |
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#### Who are the source language producers? |
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[More Information Needed] |
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### Annotations |
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#### Annotation process |
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[More Information Needed] |
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#### Who are the annotators? |
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[More Information Needed] |
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### Personal and Sensitive Information |
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[More Information Needed] |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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With the help of this dataset, one can try to understand more about software applications and what are the views and opinions of the users about them. This helps to understand more about which type of software applications are prefeered by the users and how do these applications facilitate the user to help them solve their problems and issues. |
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### Discussion of Biases |
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The reviews are only for applications that are in open-source software applications, the other sectors have not been considered here |
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### Other Known Limitations |
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[More Information Needed] |
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## Additional Information |
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### Dataset Curators |
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Giovanni Grano - (University of Zurich), Sebastiano Panichella - (University of Zurich), Andrea di Sorbo - (University of Sannio) |
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### Licensing Information |
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[More Information Needed] |
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### Citation Information |
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@InProceedings{Zurich Open Repository and |
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Archive: dataset, |
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title = {Software Applications User Reviews}, |
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authors={Grano, Giovanni; Di Sorbo, Andrea; Mercaldo, Francesco; Visaggio, Corrado A; Canfora, Gerardo; |
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Panichella, Sebastiano}, |
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year={2017} |
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} |
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### Contributions |
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Thanks to [@darshan-gandhi](https://github.com/darshan-gandhi) for adding this dataset. |