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Summary Concept Sheet Analysing Digital Culture | UvA media and information | 2025/26

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This is a final concept sheet for the Analysing Digital Culture course at Universiteit van Amsterdam, providing clear definitions of all key theoretical and practical concepts covered in the course. Topics span platform dynamics (algorithmically-driven moderation, platformisation, multi-sided markets), digital labour (gig economy, influencer work, visibility labour), creative practices (vernacular creativity, remix, memes), and critical frameworks (surveillance capitalism, digital redlining, cyberfeminism). Ideal for exam preparation and consolidating your understanding of core ADC concepts—all definitions are concise, precise, and directly aligned with course teaching.

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ADC course concepts final sheet

Ad targeting
The practice of delivering ads to specific audiences based on data such as demographics,
behaviour, interests, or location.

Micro‑targeting
A highly granular form of ad targeting that uses detailed psychographic or behavioural data
to tailor messages to very small groups or individuals.

Algorithms
Step‑by‑step computational procedures that sort, rank, recommend, and classify information
on digital platforms.

Algorithmic bias
Systematic and unfair discrimination produced by algorithms due to biased data, design
choices, or structural inequalities.

Algorithmic imaginaries
How people imagine algorithms to work — often inaccurately — shaping trust, behaviour,
and expectations.

Machine learning
A subset of AI where systems learn patterns from data to make predictions or decisions
without explicit programming.

Artificial intelligence (AI)
Technologies that perform tasks associated with human intelligence, such as pattern
recognition, prediction, or language processing.

Content moderation
Processes (human or automated) that enforce platform rules by removing, restricting, or
demoting content.

Hard moderation
Removal, bans, takedowns.

Soft moderation
Demotion, shadowbanning, warning labels, friction.

Digital redlining
The discriminatory allocation of digital resources (e.g., broadband, ads, visibility) based on
race, class, or geography.

Permissive potentates

, Platforms that appear open and participatory but retain ultimate control over rules, visibility,
and governance.

Platform exceptionalism
The belief that platforms are neutral tech companies rather than publishers, allowing them to
avoid responsibility for societal harms.

Platformisation
The expansion of platform logic — data extraction, modularity, APIs, monetisation — into
other industries (e.g., music, transport).

Multi‑sided markets
Platforms that connect different user groups (e.g., advertisers, creators, consumers) and
profit by mediating their interactions.

Editorial epistemologies
The knowledge systems and values embedded in moderation decisions — what platforms
consider “true,” “harmful,” or “acceptable.”

Gig economy
Short‑term, on‑demand labour mediated by platforms (e.g., Uber, Deliveroo), often lacking
protections and stability.

Place‑based gig work
Gig labour tied to physical locations (e.g., food delivery), shaped by geography,
infrastructure, and local regulation.

Platform labour
All forms of work performed on or for platforms, including gig work, content creation,
moderation, and data labour.

Influencer labour
The emotional, aesthetic, relational, and entrepreneurial work influencers perform to
maintain visibility and income.

Visibility labour
The continuous work required to stay seen on platforms — posting, engaging, optimising for
algorithms.

Self‑branding
The strategic crafting of a public persona to attract attention, followers, or economic
opportunities.

Self‑representation
How individuals present themselves online through images, text, and interactions.

Ownership practices
How creators claim, negotiate, or lose ownership over digital content in platform ecosystems.

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