Computational Mechanisms of Social Media Use in Youth
This project aims to develop computational models and analyze social media trace data to understand youth engagement and its neurocognitive impacts, enhancing future research frameworks.
Projectdetails
Introduction
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.
Key Limitations in Current Research
Recent meta-analyses and reviews have identified that the field is hampered by several key limitations:
- An overreliance on subjective and high-level measures, such as screen time.
- The underuse of social media trace data.
- Lack of ecologically valid experimental tasks.
- The absence of a framework for understanding social media engagement.
Proposed Solutions
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.
- Use neuroimaging to further test and refine these formal models.
Focus Areas of the Project
This project will focus on the neurocognitive development of fundamental cognitive processes that interact with the two key affordances that social media platforms provide:
- Social feedback processing.
- Social information processing.
Theoretical Framework
The computational framework is grounded in:
- Models of neurocognitive development.
- Reinforcement learning models.
- Bayesian models of belief updating.
Expected Outcomes
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.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 2.000.000 |
Totale projectbegroting | € 2.000.000 |
Tijdlijn
Startdatum | 1-11-2024 |
Einddatum | 31-10-2029 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- UNIVERSITEIT VAN AMSTERDAMpenvoerder
Land(en)
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Towards a social neuroscience of health-related decision-makingThe SOCIALCRAVING project aims to uncover brain mechanisms linking social relationships to health by developing a neurophysiological signature of social craving using fMRI and machine learning. | ERC STG | € 1.491.166 | 2023 | Details |
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The SOLAR project aims to develop a unified theoretical framework for understanding social learning mechanisms and their impact on cultural evolution and social contagion through multi-level analysis.
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The SOCIALCRAVING project aims to uncover brain mechanisms linking social relationships to health by developing a neurophysiological signature of social craving using fMRI and machine learning.
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