annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- text-scoring
- sentiment-scoring
paperswithcode_id: null
pretty_name: AppReviews
dataset_info:
features:
- name: package_name
dtype: string
- name: review
dtype: string
- name: date
dtype: string
- name: star
dtype: int8
splits:
- name: train
num_bytes: 32769079
num_examples: 288065
download_size: 42592679
dataset_size: 32769079
Dataset Card for [Dataset Name]
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: Home Page
- Repository: Repo Link
- Paper: Link
- **Leaderboard:
- Point of Contact: Darshan Gandhi
Dataset Summary
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)
Supported Tasks and Leaderboards
The dataset we provide comprises 395 different apps from the F-Droid repository, including code quality indicators of 629 versions of these 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.
Languages
The dataset is a monolingual dataset that has the messages in English.
Dataset Structure
Data Instances
The dataset consists of a message in English.
{'package_name': 'com.mantz_it.rfanalyzer', '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.", 'date': 'October 12 2016', 'star': 4}
Data Fields
- package_name: Name of the Software Application Package
- Review : Message of the user
- date: the date when the user posted the review
- star: rating provided by the user for the application
Data Splits
There is training data, with a total of 288065
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
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.
Discussion of Biases
The reviews are only for applications that are in open-source software applications, the other sectors have not been considered here
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
Giovanni Grano - (University of Zurich), Sebastiano Panichella - (University of Zurich), Andrea di Sorbo - (University of Sannio)
Licensing Information
[More Information Needed]
Citation Information
@InProceedings{Zurich Open Repository and Archive: dataset, title = {Software Applications User Reviews}, authors={Grano, Giovanni; Di Sorbo, Andrea; Mercaldo, Francesco; Visaggio, Corrado A; Canfora, Gerardo; Panichella, Sebastiano}, year={2017} }
Contributions
Thanks to @darshan-gandhi for adding this dataset.