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Media in the Online Age

Algorithms, curation and the attention economy

  • 3 things to know
  • Component 2

Overview

Term recommendation algorithm, filter bubble and what is meant by the attention economy.

What you need to know

Answer each one before you reveal it.

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Key term

What is a recommendation algorithm, what does it measure, and how do creators respond to it?

Key term

Define the term recommendation algorithm.

Key term

Which signals does a video recommendation system typically use?

Questions from this subtopic

Each one with the model answer underneath.

  1. 1

    Define the term recommendation algorithm.

    Model answer

    A recommendation algorithm is an automated system that selects what content a user sees next. Past behaviour and the behaviour of similar users drive the selection.

  2. 2

    Which signals does a video recommendation system typically use?

    Model answer

    Watch time, click-through rate, likes, comments and viewing history all feed the system. Retention across a whole video matters more than a single click.

  3. 3

    How does algorithmic curation change media language?

    Model answer

    Creators design thumbnails, titles and opening seconds to satisfy the system. Video length and upload frequency are also shaped by what the algorithm rewards.

  4. 4

    What is clickbait?

    Model answer

    Clickbait is a title or thumbnail that overstates a video's content to win a click. Short-term traffic is gained at the cost of trust.

  5. 5

    What is a filter bubble?

    Model answer

    A filter bubble is the narrowed information environment produced by personalised recommendation. A user increasingly meets material that confirms existing views.

  6. 6

    Why is the filter bubble argument contested?

    Model answer

    Research findings on how strongly personalisation narrows exposure are mixed. Some studies find that online users encounter a wider range of views than offline.

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