DGB 4: Social Media, Business Interests and Self-Image

← Digital Literacy – Year 4

Social-media platforms are communication spaces and commercial products at the same time. Advertising, data analysis and attention-based business models can influence which content is promoted and how users compare themselves with others. Students learn to separate personal choice from platform incentives and make more deliberate decisions.

Curriculum reference

Area	Classification
Competence area	Communication
Perspectives	G, I
Focus	How corporate interests influence worldviews and self-image on social media
Competence	Analyse social-media business models, advertising and attention mechanisms and make more deliberate platform and usage choices.

Learning objectives

Students can:

describe common social-media business models;
explain how targeted advertising uses user data and inferred interests;
recognise algorithmic selection and attention optimisation;
describe possible effects of filter bubbles and echo chambers;
analyse how idealised images can affect self-image and social comparison;
explain FOMO and design patterns that encourage continued use;
recognise artificial engagement such as bots or purchased interactions;
identify privacy trade-offs in social-media use;
compare platforms using transparent criteria;
develop strategies for more deliberate and balanced use.

Learning content

Business interests and platform models

Many platforms earn revenue through advertising, subscriptions, commissions or data-driven services. The provider's goal may therefore include increasing engagement, time spent and advertising effectiveness.

Targeted advertising and consumption

Behavioural signals can be used to select advertising for assumed interests. Advertising may be clearly labelled, embedded in influencer content or blended into the visual style of ordinary posts.

Algorithmic selection and attention

Ranking systems choose which posts appear prominently. Content that receives strong engagement can be favoured, which may reward emotionally intense or highly shareable material.

Worldview, filter bubbles and echo chambers

Repeated exposure to similar viewpoints can distort perceptions of how common a belief is. Group dynamics may further reinforce positions when disagreement is discouraged.

Self-image and social comparison

Curated images often show highlights rather than ordinary life. Constant comparison with idealised bodies, lifestyles or achievements can affect expectations and well-being.

FOMO and artificial belonging

Notifications, streaks, scarcity messages and visible popularity metrics can create pressure to remain active. Such features are design choices, not natural requirements of communication.

Artificial interactions

Bots, coordinated accounts or purchased likes can make ideas or products appear more popular than they really are. Popularity signals therefore need critical interpretation.

Privacy and deliberate choice

Users can compare platforms by data collection, privacy controls, advertising, moderation, interoperability and purpose. The 'best' platform depends on what someone actually needs.

Classroom activities

Audit a platform

Analyse a platform description for business model, data use, ranking and moderation.

Expected outcome: A platform profile.

Advertising or ordinary post

Classify prepared examples and identify commercial indicators.

Expected outcome: An advertising analysis.

My feed, my worldview

Use a fictional feed to trace how repeated engagement could narrow topics.

Expected outcome: A feed-path diagram.

Self-image comparison

Analyse how selection, filters and editing affect perceived normality.

Expected outcome: A reflection sheet.

Role-play a platform company

Balance goals of users, advertisers, creators, moderators and owners.

Expected outcome: A business-and-responsibility map.

Justify a platform choice

Choose a platform for a defined communication task using agreed criteria.

Expected outcome: A reasoned recommendation.

Make advertising data visible

Map which behavioural signals could be useful for targeted advertising.

Expected outcome: A data-to-advertising map.

Create a conscious-use guide

Develop practical rules for notifications, source diversity, privacy and time.

Expected outcome: A usage guide.

Influencer case analysis

Separate personal recommendation, sponsorship and platform incentives in a fictional case.

Expected outcome: A transparent analysis.

Media balance reflection

Observe usage categories and triggers for a short period without storing private content.

Expected outcome: A personal action plan.

Self-check

I understand that social media has business incentives.
I can recognise targeted advertising and attention mechanisms.
I can explain how ranking may affect what I see.
I can analyse idealised self-presentation critically.
I can compare platforms using privacy, purpose and control as criteria.
I have strategies for more deliberate use.