MATSEC SEC Media Literacy Education study materials
MATSEC SEC Media Literacy Education study resources

MATSEC SEC Media Literacy Education: Digital and Social Media, Algorithms and Data

MATSEC SEC Media Literacy Education · Work through your exam, one topic at a time.

All guide sections

Digital and Social Media, Algorithms and Data

Focus

Questions here examine how platforms shape what we see and how our data is captured, used and protected. Describe an algorithm conceptually, explain personalisation, and apply data protection principles.

Core concepts

  • Platforms as intermediaries: they host, rank and monetise content, setting rules through terms of service and moderation rather than employing journalists.
  • Affordances (boyd): persistence, replicability, scalability and searchability, plus visibility and spreadability. These explain why a post travels far beyond its intended audience.
  • Algorithms: recommendation and ranking systems predict engagement and optimise for time spent or clicks. Signals include watch time, shares, recency, your past behaviour and the behaviour of similar users. Personalisation can produce filter bubbles, though the evidence is mixed - do not overstate it.
  • Algorithms are not neutral: they encode design choices and can amplify bias or outrage.
  • Data: personal data, metadata, cookies, tracking pixels, device identifiers and profiling. GDPR principles: lawfulness, fairness, transparency, purpose limitation, data minimisation, accuracy, storage limitation, integrity and confidentiality, accountability. Rights include access, rectification, erasure and objection; consent must be freely given, specific and informed. In Malta, the Information and Data Protection Commissioner supervises.
  • Design tactics: dark patterns, infinite scroll, autoplay, streaks.

Worked example

A student searches for gym workouts, then sees fitness supplements and body-image content for weeks. Engagement signals from the search and watch time predict affinity, so the recommender boosts related content; advertising systems bid to reach that inferred profile. This is personalisation through profiling, not a conspiracy, but it raises consent, data minimisation and wellbeing issues for a young user.

Traps

  • Personifying 'the algorithm' as a single conscious agent.
  • Treating filter bubbles as proven universal fact.
  • Thinking GDPR only means cookie pop-ups.
  • Ignoring the commercial incentives behind design choices.