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.

Subsidie
€ 2.000.000
2024

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

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.
  3. Lack of ecologically valid experimental tasks.
  4. 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

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.
  2. Social information processing.

Theoretical Framework

The computational framework is grounded in:

  1. Models of neurocognitive development.
  2. Reinforcement learning models.
  3. 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

Startdatum1-11-2024
Einddatum31-10-2029
Subsidiejaar2024

Partners & Locaties

Projectpartners

  • UNIVERSITEIT VAN AMSTERDAMpenvoerder

Land(en)

Netherlands

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