Computational Mechanisms of Social Media Use in Youth
We have an urgent need to better understand the social media engagement of youth. Social media supports the specific developmental needs of youth, such as those for social connection. However, the increased sensitivity of the deve...
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Información proyecto MediaMinds
Duración del proyecto: 59 meses
Fecha Inicio: 2024-11-01
Fecha Fin: 2029-10-31
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
We have an urgent need to better understand the social media engagement of youth. Social media supports the specific developmental needs of youth, such as those for social connection. However, the increased sensitivity of the developing brain to social rewards may place youth especially at risk. In addition, youth’s sensitivity to social influence exposes another potential vulnerability, given that not all information is trustworthy. Understandably, there have been widespread fears about the impact of social media on youth. However, currently little is known about what drives youth to engage with social media or how they are impacted by it.Recent meta-analyses and reviews have identified that the field is hampered by several key limitations: 1) an overreliance on subjective and high-level measures, such as screen time, 2) the underuse of social media trace data and 3) lack of ecologically valid experimental tasks, and 4) the absence of a framework for understanding social media engagement. Here I address that challenge by developing novel computational models that provide a theoretical formalization of the complex interactions between the developing cognitive processes and social media affordances. In addition, I will analyse social media trace data, develop novel ecologically valid experimental tasks, and use neuroimaging to further test and refine these formal models. This project will focus on the neurocognitive development of fundamental cognitive processes that interact with the two key affordances that social media platforms provide: 1) social feedback processing and,2) social information processing.The computational framework is grounded in 1) models of neurocognitive development, 2) reinforcement learning models, and 3) Bayesian models of belief updating. Our findings will significantly advance our understanding of the social media engagement of youth on the mechanistic level, and will provide a fruitful framework and toolbox for future studies.