Authors:
Jonathan Kuspil
1
;
João Ribeiro
2
;
Gislaine Leal
1
;
Guilherme Guerino
1
;
2
and
Renato Balancieri
1
;
2
Affiliations:
1
State University of Maringá (UEM), Maringá, Brazil
;
2
State University of Paraná (UNESPAR), Apucarana, Brazil
Keyword(s):
Mobile Application, Graphical User Interface, Metadata Datasets, Design Mining, App Datasets.
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.
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