APG5457 Digital cultures and platforms
The Complete Study & Assessment Guide · S2 2026APG5457 Overview
- Monash University
- Semester 2, 2026
- Postgraduate level
- Six-week block mode
APG5457 Digital cultures and platforms examines how digital platforms reshape media and communications industries, cultural circulation, work and everyday use.
- Assessment Presentation, in-class test and platform fieldwork
- Core method Connect a specific observation to an institutional mechanism
- Major task Build a documented auto-ethnographic evidence trail
- Critical lens Ask who sets rules, captures value and bears risk
How APG5457 is assessed
| Component | Weight | Format |
|---|---|---|
| Assessment 1: Work-In-Progress Video Presentation | 30% | Recorded 3 to 5 minute presentation of initial platform research and fieldwork progress |
| Assessment 2: In-class test | 20% | Written test in the fifth class week on lectures and readings from the first five class weeks; handwritten notes permitted |
| Assessment 3: Platform auto-ethnography fieldwork study | 50% | Reflective analysis with screenshots, references, fieldnotes and supporting documentation |
Current APG5457 dates
| Date | Item | Control |
|---|---|---|
| October 4, 2026 | Work-In-Progress Video Presentation | Published due date for the Semester 2, 2026 task. |
| November 5, 2026 | Platform auto-ethnography fieldwork study | Published due date for the Semester 2, 2026 task. |
Dates are as published in the Semester 2, 2026 Moodle assessment pages. Confirm exact deadlines and submission settings in the live LMS.
What APG5457 covers
Follow the unit from web commercialisation and platform capitalism through labour, algorithms and cultural production to platform decline and institutional alternatives.
Commercialisation of the Web
Public-interest networks, web commercialisation, Californian Ideology, neoliberalism and the rise of advertising and user-data models.02The Rise of Platforms
Platform capitalism, data extraction, network effects, cross-subsidisation, stickiness, chokepoints and platform rhetoric.03Labour in the Platform Economy
Lean business models, gig and crowd work, creator precarity, digital labour, risk transfer and platform control.04Algorithms, Targeting and Opacity
Recommendation, ranking, targeting, opaque systems, fieldnote design and careful auto-ethnographic inference.05Platformised Cultural Production
How platforms reshape cultural making, distribution, discovery, consumption, metrics and competing forms of value.06Platform Decline and Alternatives
Platform lifecycles, degradation, user migration, shadow economies and institutional alternatives to dominant models.The unit begins historically, asking how an internet associated with public access, collaboration and participation became increasingly commercialised and privatised. It then treats platforms as business models and intermediaries: firms that organise interactions, collect behavioural traces, rank visibility and convert participation into economic value.
The course moves from institutions to lived experience.
Platform labour includes gig and crowd work, creator activity and the data-producing actions of users. Algorithmic systems order exposure while remaining difficult to inspect, so the unit develops careful methods for studying recommendations without pretending to see inside the model.
Auto-ethnography provides that method: students record their own interactions, preserve screenshots and fieldnotes, reflect on their participation, and connect specific encounters to scholarship on platform power.
Cultural production remains central throughout. Platforms alter how films, television, music and other cultural works are made, distributed, discovered, consumed and valued.
The final topic treats platforms as unstable rather than permanent, examining decline, deterioration, migration and possibilities beyond dominant corporate forms. Across the unit, the strongest analysis names an actor, identifies a rule or business mechanism, supplies concrete evidence, recognises uncertainty and explains the wider significance for media, labour or culture.
Audit a fictional recommendation feed without overclaiming
- 2State the visible evidence: later ordering gives concentration playlists greater prominence and repeats a related visual category.
- 2Connect the observation to the logged behaviour while distinguishing timing from proof of causation.
- 2Apply ranking and data-extraction concepts to explain how activity may become a signal for ordering.
- 2Add a boundary and significance: the precise mechanism is opaque, while the interface still shapes how the listener encounters and understands available music.
Key terms
- Platform capitalism
- A framework for analysing platform firms as capitalist businesses that extract, refine and monetise data while organising exchange.
- Network effects
- A process through which a service may become more valuable as participation grows, reinforcing scale and concentration.
- Cross-subsidisation
- Funding one service or user group through revenue from another part of the business in order to support adoption or dominance.
- Chokepoint power
- Control gained by an intermediary that becomes a difficult-to-avoid gateway between producers and audiences or other dependent groups.
- Digital labour
- Work and value-producing activity carried out through digital systems, including visible paid work and less visible user participation.
- Digital Taylorism
- Data-intensive measurement and control that decomposes, monitors and directs work through platform systems.
- Algorithmic opacity
- The difficulty outsiders face when trying to inspect the inputs, objectives and operations of a ranking or recommendation system.
- Auto-ethnography
- A research method that connects documented personal experience to critical analysis of broader cultural and institutional relations.
- Platformisation
- The reorganisation of cultural or social fields around platform infrastructures, business models, data practices and governance.
APG5457 FAQ
How is the unit assessed?
The current structure is a Work-In-Progress Video Presentation worth 30%, an In-class test worth 20%, and a Platform auto-ethnography fieldwork study worth 50%. The numeric weights total 100% across the unit.
What notes can I take into the in-class test?
The task page permits handwritten notes. Laptops, phones, printouts, lecture slides and printed readings are not permitted, so prepare concise handwritten concept, mechanism and case maps.
What should a platform audit include?
Identify the service and participants, revenue source, data pathway, retention design, ranking or access rules, network effects, switching frictions and the distribution of benefits and risks.
What makes auto-ethnography rigorous?
Use a defined observation period, regular fieldnotes, timestamped screenshots, an action log, reflexive attention to your own involvement, scholarship-based interpretation and explicit limits on causal claims.
Can a changed feed prove what the algorithm did?
A changed feed is evidence about visible ordering, not direct access to the model. Build a pattern across captures, document intervening behaviour and use calibrated language for the explanation.
How should a reflective vignette end?
Move from the situated encounter to its wider significance. Name the platform relation involved, apply a concept that explains the mechanism, and state what the experience reveals about digital culture or power.
How to prepare for the assessments
Study APG5457 by building causal maps rather than isolated definitions. For each concept, record the actors, institutional rule, mechanism, outcome and boundary. Attach one course-supported case and one counter-case so that the concept remains analytical rather than moral shorthand.
For the in-class test, convert each topic into handwritten notes organised by distinction and mechanism: public promise versus commercial arrangement, network effects versus stickiness, independence versus control, visible recommendation versus hidden model, platform visibility versus cultural value, and technological architecture versus institutional governance. For the major study, begin with evidence management.
Keep baseline and later screenshots, timestamp ordinary actions, separate observation from interpretation in fieldnotes, and retain drafts. Build each vignette around a concrete interface encounter, then use scholarship to explain how revenue, data, ranking, labour or cultural production structures it. Review every causal verb before submission and calibrate claims that exceed direct observation.
The strongest conclusion returns to the unit's political economy by identifying who sets the rules, who captures value, who bears uncertainty and which institutional alternative would change that distribution.
