Information Diffusion Modeling in Social Networks: A Comparative Analysis of Delay Mechanisms Using Population Dynamics

Bakenova K. Kuznetsov O. Artyshchuk I. Shaikhanova A. Shevchuk R. Orobchuk O.
June 2025 Multidisciplinary Digital Publishing Institute (MDPI)

Applied Sciences (Switzerland)
2025 #15 Issue 11

This study presents a comprehensive analysis of information diffusion in social networks with time delay mechanisms. We first analyze real Reddit thread data, identifying limitations in the sample size. To overcome this, we develop synthetic network models with varied structural properties. Our approach tests three delay types (constant, uniform, exponential) across different network structures, using machine learning models to identify key factors influencing information coverage. The results show that spread probability consistently impacts diffusion across all datasets. Gradient Boosting models achieve R² = 0.847 on synthetic data. Random networks with a constant delay mechanism and high spread probability (0.4) maximize coverage. When verified against test data, peak speed time emerges as the strongest predictor (r = 0.995, p < 0.001). Our findings provide practical recommendations for optimizing information spread in social networks and demonstrate the value of integrating real and synthetic data in diffusion modeling.

comparative modeling , information diffusion , machine learning , population dynamics , Reddit threads , social networks , synthetic networks , time delay mechanisms

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Department of Information Security, L.N. Gumilyov Eurasian National University, Satpayev 2, Astana, 010008, Kazakhstan
Department of Theoretical and Applied Sciences, eCampus University, Via Isimbardi 10, Novedrate, 22060, Italy
Department of Intelligent Software Systems and Technologies, School of Computer Science and Artificial Intelligence, Karazin Kharkiv National University, 4 Svobody Sq., V.N, Kharkiv, 61022, Ukraine
Department of Data Science, University of the National Education Commission, Krakow, 30-084, Poland
Department of Computer Science and Automatics, Faculty of Mechanical Engineering and Computer Science, University of Bielsko-Biala, Bielsko-Biala, 43-300, Poland
Department of Computer Science, West Ukrainian National University, Ternopil, 46009, Ukraine
Department of Cybersecurity, Ternopil Ivan Puluj National Technical University, Ternopil, 46001, Ukraine

Department of Information Security
Department of Theoretical and Applied Sciences
Department of Intelligent Software Systems and Technologies
Department of Data Science
Department of Computer Science and Automatics
Department of Computer Science
Department of Cybersecurity

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