Faculty Mentor
Dr. Ahmed Al-Taweel
Location
Russell Union Ballroom
Type of Research
Completed
Session Format
Poster Presentation
College
College of Science & Mathematics
Department
Mathematical Science
Abstract
Digital media communication technologies have changed how people organize and act together. During the Generation Z event, social media platforms (e.g., X, YouTube, Facebook) played a major role in spreading information and mobilizing collective actions online and offline. In this work, we modified a mathematical dynamic model of the social media mob using an optimal control technique to adjust the rate of spread in response to social interactions. We examined the susceptible-quarantined-counter-infective-recovered (SQCIR) epidemiology model on a YouTube dataset covering Gen-Z data spread in Nepal from 8 to 13 September 2025. Using high-temporal-resolution real-world social media data will help to predict near-real-time campaign. Data collection focused on key terms, such as “genzmovement” and “NepalProtests,” to track mob activity trends during the life-cycle campaign. Qualitative analyses, including the mob-free equilibrium (MFE) point of social media, the endemic equilibrium point, and the basic reproduction number R0, were estimated. Stability analysis shows that mob-free social media equilibrium is locally asymptotically stable when R0 < 1, whereas a unique endemic equilibrium exists and is stable when R0 > 1. Numerical examples and sensitivity analyses of the fitting parameters are established. Moreover, the Caputo Fractional operator with various parameter values is used to examine the effect of social networks on the transmission in the data set. Finally, two time-dependent controls were added to the basic model to yield an optimal control model.
Program Description
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DOI
10.20429/GS4.2026.020
Start Date
4-23-2026 2:00 PM
End Date
4-23-2026 4:00 PM
Recommended Citation
Alhassan, Tahidu, "Optimal Control Analysis of Mob Dynamics Using Generation Z YouTube Channel Behavior" (2026). GS4 Student Scholars Symposium. 170.
https://digitalcommons.georgiasouthern.edu/research_symposium/2026/2026/170
Optimal Control Analysis of Mob Dynamics Using Generation Z YouTube Channel Behavior
Russell Union Ballroom
Digital media communication technologies have changed how people organize and act together. During the Generation Z event, social media platforms (e.g., X, YouTube, Facebook) played a major role in spreading information and mobilizing collective actions online and offline. In this work, we modified a mathematical dynamic model of the social media mob using an optimal control technique to adjust the rate of spread in response to social interactions. We examined the susceptible-quarantined-counter-infective-recovered (SQCIR) epidemiology model on a YouTube dataset covering Gen-Z data spread in Nepal from 8 to 13 September 2025. Using high-temporal-resolution real-world social media data will help to predict near-real-time campaign. Data collection focused on key terms, such as “genzmovement” and “NepalProtests,” to track mob activity trends during the life-cycle campaign. Qualitative analyses, including the mob-free equilibrium (MFE) point of social media, the endemic equilibrium point, and the basic reproduction number R0, were estimated. Stability analysis shows that mob-free social media equilibrium is locally asymptotically stable when R0 < 1, whereas a unique endemic equilibrium exists and is stable when R0 > 1. Numerical examples and sensitivity analyses of the fitting parameters are established. Moreover, the Caputo Fractional operator with various parameter values is used to examine the effect of social networks on the transmission in the data set. Finally, two time-dependent controls were added to the basic model to yield an optimal control model.
