Datasets on Mobile App Metadata and Interface Components to Support Data-Driven App Design

Jonathan Kuspil, João Ribeiro, Gislaine Leal, Guilherme Guerino, Guilherme Guerino, Renato Balancieri, Renato Balancieri

2024

Abstract

The global mobile device market currently encompasses 6.5 billion users. Therefore, standing out in the competitive scenario of application stores such as the Google Play Store (GPlay) requires, among several factors, great concern with the User Interface (UI) of the apps. Several datasets explore UI characteristics or the metadata present in GPlay, which developers and users write. However, few studies relate these data, limiting themselves to specific aspects. This paper presents the construction, structure, and characteristics of two Android app datasets: the Automated Insights Dataset (AID) and the User Interface Depth Dataset (UID). AID compiles 48 different metadata from the 200 most downloaded free apps in each GPlay category, totaling 6400 apps, while UID goes deeper into identifying 7540 components and capturing 1948 screenshots of 400 high-quality apps from AID. Our work highlights clear selection criteria and a comprehensive set of data, allowing metadata to be related to UI characteristics, serving as a basis for developing predictive models and understanding the current complex scenario of mobile apps, helping researchers, designers, and developers.

Paper Citation

in Harvard Style

Kuspil J., Ribeiro J., Leal G., Guerino G. and Balancieri R. (2024). Datasets on Mobile App Metadata and Interface Components to Support Data-Driven App Design. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-692-7, SciTePress, pages 425-432. DOI: 10.5220/0012740600003690

in Bibtex Style

@conference{iceis24,
author={Jonathan Kuspil and João Ribeiro and Gislaine Leal and Guilherme Guerino and Renato Balancieri},
title={Datasets on Mobile App Metadata and Interface Components to Support Data-Driven App Design},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2024},
pages={425-432},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012740600003690},
isbn={978-989-758-692-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Datasets on Mobile App Metadata and Interface Components to Support Data-Driven App Design
SN - 978-989-758-692-7
AU - Kuspil J.
AU - Ribeiro J.
AU - Leal G.
AU - Guerino G.
AU - Balancieri R.
PY - 2024
SP - 425
EP - 432
DO - 10.5220/0012740600003690
PB - SciTePress