CHAITok: A Proof-of-Concept System Supporting Children's Sense of Data Autonomy on Social Media

Title of the Paper

CHAITok: A Proof-of-Concept System Supporting Children’s Sense of Data Autonomy on Social Media

Paper Information

• Subject Area: Human-Computer Interaction (HCI), Children's Digital Rights, and Social Media Data Privacy
• Keywords: Children, Data Autonomy, Social Media, Human-Computer Interaction, Digital Rights, Datafication, Recommendation Algorithms, Online Privacy Protection, Social Media Education, Algorithm Transparency

Research Background and Problem Statement

• Identified Issues or Challenges: Current social media data mining practices pose a threat to children's autonomy. Platforms' extensive data collection and usage not only infringe on user privacy but also influence children's behavior and cognitive development through algorithmic recommendations. Meanwhile, parents, as guides and protectors, are increasingly limited in their roles amidst rapid technological advancements.
• Significance: Datafication not only affects the presentation of online content to children but may also trigger behavioral engineering and opinion manipulation. Given the potential threats of datafication to children's physical and mental health as well as their autonomy, there is an urgent need to enhance children's agency and control over their data through design and technological interventions.
• Research Motivation and Related Work: Existing research on children's autonomy has primarily focused on issues such as screen time, online safety, and inappropriate content detection, while neglecting the deeper impacts of social media datafication. This study aims to expand children's understanding of datafication and digital rights through technological and design interventions, empowering them with data autonomy.

Solution

• Proposed Solution: Development of a prototype application called CHAITok, an Android-based mobile app designed to enhance children's data autonomy on social media platforms.
• Innovations:
  • Introduced the concept of data autonomy encompassing three stages: "data collection, data processing, and data inference."
  • Designed an interactive control panel for children, enabling configuration of data collection types, algorithm weights, and behavior predictions.
  • Included educational features, such as a "WHAT IS" information module and an option reflection panel, to help children understand the datafication process.
• Implementation Steps and Key Technologies:
  1. Defining the Scope of Data Autonomy: Proposed a working definition clarifying the three stages—data collection, processing, and inference.
  2. Design and Features:
     • A data interaction panel appears after every 15 recommended videos.
     • Provides switches for data types, algorithm weight adjustments, and interest category controls.
  3. Implementation Method: Developed the program using Android Studio, integrating Google Firebase to store interaction data and recommendation algorithms. Ensured content safety and participant privacy (anonymous account settings).
  4. User Research and Validation: Conducted a total of 27 user research sessions involving 109 children aged 10 to 13.

Research Outcomes

• Specific Findings:
  1. Discovered that children have limited understanding of the datafication process but desire more agency.
  2. CHAITok significantly improved children's perceptions of data security, control, and respect. Participants reported enhanced trust and a sense of control over algorithms.
  3. Provided deeper insights into children's understanding of data autonomy: from controlling information dissemination to constructing digital identities.
• Advantages:
  • Compared to existing social media platforms, CHAITok significantly improved children's interaction experience through transparent operations and guided design.
  • Supported children's development of cognitive, behavioral, and emotional autonomy while helping them avoid potential algorithmic manipulation and unhealthy content recommendations.
• Experimental and Evaluation Results:
  • The pop-up designs for the data collection, processing, and inference stages were well-received by children, who clearly perceived changes in recommended video results based on their settings.
  • Children significantly improved their understanding of social media datafication behaviors through various panels.
  • Found that children were willing to reflect on and adjust their behavior after using CHAITok to avoid potential risks of content dependency and data misuse.
• Limitations and Future Directions:
  • Limitations: The selected school sample may exhibit conservative tendencies; the simplified datafication model designed for the study may not fully cover the complexities of real-world data practices.
  • Future Directions:
    • Conduct long-term observations of children's autonomy development pathways and design features that further encourage reflection.
    • Incorporate parents or teachers into the system to achieve collaborative design.
    • Motivate social media developers to continuously optimize child-friendly algorithms and data practices.

This study and system design reinforce the argument that children's data autonomy is a core component of their digital rights. It also provides a clear practical pathway to promote healthier technological experiences for children in a data-driven society.