Graph-Based Simulation and Modeling of Screentime Data: A Comparative Study of Gaussian and Random Graphical Approaches

Fatemeh Sarasir; Vilda Purutcuoglu; Ahmet Bursalı

doi:10.54287/gujsa.1835295

Graph-Based Simulation and Modeling of Screentime Data: A Comparative Study of Gaussian and Random Graphical Approaches

Abstract

Graphical models provide a powerful framework for analyzing complex dependence structures among multiple variables, allowing researchers to uncover direct relationships and reduce spurious correlations in high-dimensional data. This study investigates two prominent approaches—the Gaussian graphical model (GGM) and random graphical model (RGM)—to compare their performance in modeling sparse networks under both simulated and real-world conditions. The GGM method emphasizes computational efficiency through ℓ₁-regularized precision estimation, while RGM adopts a probabilistic view that incorporates uncertainty in graph structures. Through simulation experiments, we evaluate the accuracy, stability, and robustness of each method across varying sample sizes and dimensionalities. A real-world application utilizing smartphone screentime data further illustrates how network-based analyses can reveal behavioral patterns across app usage features, such as time spent and notification frequency. This paper provides the first direct comparison of GGM and RGM on real screentime data, addressing a gap in prior work that considered only pairwise associations without evaluating these models side by side. To enhance data quality, we integrate the Gramian angular field (GAF) technique to convert time-series data into visual similarity matrices, enabling the removal of highly redundant days. Reapplying prominent approaches on the refined dataset yields clearer insights into inter-app dependencies, highlighting methodological trade-offs and complementary strengths for analyzing complex behavioral data.

Keywords

Supporting Institution

Scientific and Technological Research Council of Turkey (TÜBİTAK)

Project Number

5240032

Ethical Statement

None

Thanks

The authors would like to thank the Scientific and Technological Research Council of Turkey (TÜBİTAK) project grant with project number 5240032.

References

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Details

Primary Language

English

Subjects

Data Engineering and Data Science

Journal Section

Research Article

Authors

Fatemeh Sarasir
0009-0003-5432-1352
Türkiye

Vilda Purutcuoglu ^*
0000-0002-3913-9005
Türkiye

Ahmet Bursalı
0000-0001-7050-769X
Türkiye

Publication Date

June 30, 2026

Submission Date

December 9, 2025

Acceptance Date

May 24, 2026

Published in Issue

Year 2026 Volume: 13 Number: 2

DOI

https://doi.org/10.54287/gujsa.1835295

IZ

https://izlik.org/JA76PB48WA

Cite

RIS / Bibtex

APA

Sarasir, F., Purutcuoglu, V., & Bursalı, A. (2026). Graph-Based Simulation and Modeling of Screentime Data: A Comparative Study of Gaussian and Random Graphical Approaches. Gazi University Journal of Science Part A: Engineering and Innovation, 13(2), 522-541. https://doi.org/10.54287/gujsa.1835295

AMA

1.Sarasir F, Purutcuoglu V, Bursalı A. Graph-Based Simulation and Modeling of Screentime Data: A Comparative Study of Gaussian and Random Graphical Approaches. GU J Sci, Part A. 2026;13(2):522-541. doi:10.54287/gujsa.1835295

Chicago

Sarasir, Fatemeh, Vilda Purutcuoglu, and Ahmet Bursalı. 2026. “Graph-Based Simulation and Modeling of Screentime Data: A Comparative Study of Gaussian and Random Graphical Approaches”. Gazi University Journal of Science Part A: Engineering and Innovation 13 (2): 522-41. https://doi.org/10.54287/gujsa.1835295.

EndNote

Sarasir F, Purutcuoglu V, Bursalı A (June 1, 2026) Graph-Based Simulation and Modeling of Screentime Data: A Comparative Study of Gaussian and Random Graphical Approaches. Gazi University Journal of Science Part A: Engineering and Innovation 13 2 522–541.

IEEE

[1]F. Sarasir, V. Purutcuoglu, and A. Bursalı, “Graph-Based Simulation and Modeling of Screentime Data: A Comparative Study of Gaussian and Random Graphical Approaches”, GU J Sci, Part A, vol. 13, no. 2, pp. 522–541, June 2026, doi: 10.54287/gujsa.1835295.

ISNAD

Sarasir, Fatemeh - Purutcuoglu, Vilda - Bursalı, Ahmet. “Graph-Based Simulation and Modeling of Screentime Data: A Comparative Study of Gaussian and Random Graphical Approaches”. Gazi University Journal of Science Part A: Engineering and Innovation 13/2 (June 1, 2026): 522-541. https://doi.org/10.54287/gujsa.1835295.

JAMA

1.Sarasir F, Purutcuoglu V, Bursalı A. Graph-Based Simulation and Modeling of Screentime Data: A Comparative Study of Gaussian and Random Graphical Approaches. GU J Sci, Part A. 2026;13:522–541.

MLA

Sarasir, Fatemeh, et al. “Graph-Based Simulation and Modeling of Screentime Data: A Comparative Study of Gaussian and Random Graphical Approaches”. Gazi University Journal of Science Part A: Engineering and Innovation, vol. 13, no. 2, June 2026, pp. 522-41, doi:10.54287/gujsa.1835295.

Vancouver

1.Fatemeh Sarasir, Vilda Purutcuoglu, Ahmet Bursalı. Graph-Based Simulation and Modeling of Screentime Data: A Comparative Study of Gaussian and Random Graphical Approaches. GU J Sci, Part A. 2026 Jun. 1;13(2):522-41. doi:10.54287/gujsa.1835295