The Broadcast Era
The Digital Revolution
Algorithms & Filter Bubbles
Platforms & Power
The Data Economy & AI
100

What does the “broadcast era” refer to in media history?

A time (roughly 1950s–1990s) when media was produced by a few organisations and consumed by mass audiences through TV, radio, and print.

100

What is Web 1.0?

The early, static web where users could only read content created by a few publishers.

100

Define an algorithm.

A set of programmed instructions that determine what content a user sees online.

100

Name one political or cultural influence Facebook has had.

It has shaped elections, movements (e.g., #MeToo, Arab Spring), and how news spreads.

100

Define “surveillance capitalism.”

A system where companies collect personal data to predict and influence behaviour for profit.

200

How did audiences engage with media during the broadcast era?

They were largely passive consumers; content was one-way, with little audience feedback or interaction.

200

What defines Web 2.0?

The interactive, user-driven web where people create and share content (e.g., social media).

200

How do social media algorithms shape our experience?

They prioritise content based on engagement, showing users more of what they interact with.

200

What was one key claim from the Wall Street Journal TikTok investigation?

TikTok’s algorithm quickly learns user preferences and can push users into “rabbit holes” of specific content.

200

Give an example of surveillance capitalism in action.

Google or Facebook tracking user activity to target advertising.

300

Compare audience participation in the broadcast era to today.

Broadcast era = limited control; Today = interactive, participatory culture with user-generated content.

300

What major change occurred between Web 1.0 and Web 2.0? (include key term for users)

Users became both producers and consumers (“prosumers”).

300

Who is Eli Pariser and what theory is he known for?

He proposed the concept of the “filter bubble” — users are trapped in personalised information environments.

300

How does TikTok’s recommendation system differ from traditional media programming?

It is fully personalised — every user’s “For You Page” is unique and data-driven.

300

How is AI being used in media production?

Some ways include in scriptwriting, video editing, even AI actors - e.g. Tilly Norwood

400

Explain how advertising influenced the content and scheduling of programs during the broadcast era.

Advertisers funded programs and influenced what aired; popular shows were scheduled for peak audience times to maximise exposure, shaping content to appeal to target demographics.

400

How did Web 2.0 change audience power?

It gave audiences the ability to influence, remix, and distribute content globally.

400

What is a danger of living in a filter bubble?

It can reinforce biases, reduce exposure to diverse perspectives, and polarise audiences.

400

How has Facebook changed audience engagement with news?

Audiences consume news through algorithmic feeds rather than traditional editorial gatekeeping.

400

List one advantage and one disadvantage of AI in media.

Advantage: Efficiency and cost-effective; Disadvantage: Job loss.

500

How did the limited choice of channels in the broadcast era affect audience behaviour and social experiences?

With few channels, audiences often watched the same programs, creating shared cultural moments (e.g., live sports, prime-time shows) and strong collective experiences.

500

Give one way Web 2.0 technologies have transformed media institutions.

Traditional media now rely on social platforms for distribution and engagement, shifting power to tech companies.

500

Give an example of how algorithms contribute to political polarisation.

Recommendation systems on YouTube or TikTok can push users toward more extreme or one-sided content based on engagement.

500

Discuss how platforms like Facebook or TikTok act as both media distributors and data collectors.

They control both what content is seen and harvest user data to refine advertising and influence content flow.

500

How might AI and data collection together shape future audience experiences?

They may create ultra-personalised media environments.

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