Competition Law and Cognitive Engagement Platform Concentration

1. Introduction

Cognitive engagement platforms are digital platforms whose principal competitive asset is their ability to capture, retain, measure, and monetise users’ attention, interaction, behavioural data, and engagement. Examples include social-media platforms, short-video services, recommendation platforms, online communities, search and content-discovery services, gaming/social ecosystems, and increasingly AI-mediated engagement platforms.

Competition concerns arise when a small number of platforms accumulate control over:

• user attention and engagement;
• behavioural and interaction data;
• recommendation algorithms;
• content-distribution channels;
• advertising demand and supply;
• creators and influencers;
• app and device ecosystems;
• identity and authentication systems;
• social graphs and network effects; and
• complementary services.

The legal issue is therefore not simply whether a platform has many users. The central question is whether concentration of engagement, data, network effects and distribution power enables the platform to restrict competition or entrench its position.

Modern digital competition regimes increasingly recognise these ecosystem effects. For example, Germany's Section 19a GWB allows enhanced scrutiny of companies with paramount significance across markets, while the EU Digital Markets Act imposes ex-ante obligations on designated gatekeepers.

2. Meaning of Cognitive Engagement Platform Concentration

A. Cognitive engagement

"Cognitive engagement" refers broadly to the user's attention and interaction with a platform, including:

• viewing;
• searching;
• scrolling;
• clicking;
• commenting;
• sharing;
• liking;
• messaging;
• watching;
• gaming;
• creating content;
• responding to recommendations; and
• interacting with AI systems.

The economic value comes from converting these interactions into data, advertising opportunities, transactions, subscriptions or ecosystem dependence.

B. Platform concentration

Platform concentration exists when a relatively small number of platforms control a substantial proportion of:

1. users;
2. engagement time;
3. advertising inventory;
4. creator access;
5. relevant behavioural data;
6. distribution channels; or
7. complementary digital services.

A conventional market-share analysis can therefore be insufficient.

For example:

Platform A may have only 45% of registered users but 80% of daily engagement and most valuable behavioural data.

Its competitive significance may consequently be greater than its conventional user-market share suggests.

3. Relevant Competition-Law Framework

A. Abuse of dominance

The principal concern is whether a dominant platform uses its position to exclude competitors.

Possible conduct includes:

• self-preferencing;
• tying and bundling;
• discriminatory ranking;
• exclusionary algorithms;
• discriminatory access to APIs;
• restrictions on interoperability;
• data leveraging;
• exclusivity arrangements;
• predatory pricing;
• refusal to provide access;
• discriminatory advertising access; and
• leveraging dominance from one digital market into another.

B. Network effects

Cognitive engagement platforms often exhibit strong direct and indirect network effects.

More users → more interaction → more data → better recommendations → greater engagement → more advertisers/creators → more content → more users.

This can produce a reinforcing cycle:

Users → Engagement → Data → Algorithmic improvement → Better targeting → More creators/advertisers → More users

Once established, such a feedback loop can make entry difficult even where a technically comparable competitor could build the same basic software.

4. Data as a Source of Market Power

Data can constitute an important competitive input.

A large engagement platform can accumulate:

• search histories;
• viewing histories;
• social relationships;
• location information;
• purchasing behaviour;
• interests;
• interaction patterns;
• advertising responses; and
• inferred preferences.

The competitive concern becomes stronger when the platform can combine data across several services.

The German Bundeskartellamt's Google proceedings expressly recognised that data collection and combination can contribute to digital market power and concluded that Google's competitors may face competitive disadvantages from access limitations to data.

5. Algorithmic Recommendation and Engagement Concentration

Recommendation algorithms are particularly important.

A platform may control:

Content → Ranking → User attention → Data generation → Advertising value

A dominant platform could theoretically disadvantage competitors by:

• lowering their ranking;
• restricting recommendations;
• favouring its own content;
• favouring affiliated services;
• manipulating discoverability;
• imposing discriminatory eligibility requirements; or
• using data generated by competing businesses to improve its own competing service.

The competition-law analysis must distinguish legitimate algorithmic improvement from exclusionary conduct.

6. Six Important Case Laws

1. FTC v. Meta Platforms, Inc. — United States

The Federal Trade Commission's litigation concerning Meta's acquisitions of Instagram and WhatsApp illustrates an important theory of platform concentration.

The competition concern involved the possibility that acquisitions of emerging or potentially disruptive social platforms could eliminate future competitive constraints.

Significance

The case demonstrates that competition authorities may examine:

• nascent competition;
• network effects;
• user engagement;
• data advantages;
• innovation competition; and
• acquisitions of potential competitors.

For cognitive-engagement markets, the important lesson is that competition may be harmed before a smaller platform becomes a fully developed substitute.

2. Google Search / Google Shopping — European Union

The European Commission's Google Shopping case concerned Google's treatment of its comparison-shopping service within general search results.

The underlying competition issue was whether Google leveraged its dominant position in general search to favour its own specialised service.

Relevance to cognitive engagement

Search ranking determines:

• what users see;
• what they click;
• where attention flows; and
• which competing services receive visibility.

Thus, ranking can function as a competitive bottleneck.

The case provides an important analogy for engagement platforms where algorithmic ranking determines the distribution of user attention.

3. Google Android — European Union

The Google Android proceedings addressed Google's practices concerning Android devices and associated applications.

The case illustrates how control over an important platform layer can be leveraged into adjacent markets.

Cognitive-engagement relevance

A platform controlling:

Operating system → App distribution → Search → Applications → User data

can influence the competitive conditions faced by downstream services.

The case therefore demonstrates the importance of ecosystem leverage rather than analysing each digital service in isolation.

4. Bundeskartellamt v. Facebook/Meta — Germany

The German Facebook data-combination proceedings are particularly relevant.

The Bundeskartellamt examined Facebook's ability to combine user information collected from Facebook with information from other sources.

The authority ultimately prohibited the relevant data-combination practice subject to its legal framework.

The case is significant because it connected data-processing practices with competition law and market power. The Bundeskartellamt continues to identify Meta as a company of paramount significance for competition across markets under Section 19a GWB.

Principle

Where a platform possesses substantial market power, control over user data may become a competition concern when it strengthens ecosystem advantages or impedes effective competition.

5. Shenzhen Weiyuanma Software Development Co. Ltd. v. Tencent — China

This Chinese case is particularly relevant to platform competition.

The Chinese Supreme People's Court addressed abuse-of-dominance issues involving Tencent and explained that, for comprehensive Internet platforms, the relevant market should be analysed with attention to the particular service targeted by the alleged abusive conduct.

The Court stressed the importance of distinguishing different services rather than automatically treating the entire Internet platform as one relevant market.

Significance

The case provides an important methodological principle:

A large digital ecosystem does not automatically constitute one relevant market.

For cognitive-engagement platforms, regulators may therefore examine separately:

• social networking;
• messaging;
• gaming;
• advertising;
• content distribution;
• payment services; and
• other platform services.

6. Alibaba — China

The SAMR Alibaba case is an important Chinese platform-economy precedent.

Alibaba was investigated for conduct involving the practice commonly described as "choose one from two", under which merchants were allegedly required to deal exclusively with one platform.

SAMR imposed a substantial administrative penalty.

Cognitive-engagement relevance

The case demonstrates how a platform can use accumulated ecosystem power to restrict merchants' ability to multi-home.

For engagement platforms, analogous concerns could arise where:

• creators are required to remain exclusive;
• advertisers cannot use competing platforms;
• influencers face discriminatory treatment for cross-platform activity; or
• businesses are penalised for distributing content elsewhere.

The Alibaba decision is widely regarded as a landmark development in China's enforcement against large digital platforms.

7. Additional Relevant Authorities

A. Amazon — Germany

The Bundeskartellamt determined that Amazon possessed paramount significance for competition across markets under Section 19a GWB, and the Federal Court of Justice upheld that determination in 2024.

Although Amazon is principally an e-commerce ecosystem, the case illustrates the broader principle that multi-market ecosystem power can justify enhanced competition scrutiny.

B. Google — Germany

The Bundeskartellamt's Section 19a proceedings against Google examine various ecosystem practices, including data processing, Google News Showcase, Google Maps Platform and automotive services.

This is particularly relevant to engagement platforms because Google operates multiple interconnected services capable of generating large volumes of behavioural information.

C. Google — EU Digital Markets Act

The EU's DMA provides an ex-ante model rather than waiting exclusively for conventional abuse-of-dominance proceedings.

The Commission's current gatekeeper framework covers services such as Google Search, YouTube, TikTok, Facebook, Instagram, WhatsApp and Messenger.

In July 2026, the Commission fined Google €460 million over alleged self-preferencing in Search and €430 million over non-compliant steering practices in Google Play.

These developments demonstrate how competition regulation increasingly focuses on control over digital gateways and user access.

8. Market-Definition Problems

Traditional market definition becomes complicated because engagement platforms may offer services at a monetary price of zero.

For example:

Users pay no subscription fee, but provide attention and behavioural data.

Consequently, competition authorities may consider:

User-side market

Social networking or content engagement.

Advertising-side market

Digital advertising inventory.

Creator-side market

Access to users and monetisation.

Data-side market

Access to valuable behavioural information.

Distribution-side market

Access to platform users.

A platform can consequently possess significant power even when the consumer-facing service is nominally free.

9. Multi-Sided Market Analysis

Cognitive engagement platforms generally connect multiple groups:

Competition authorities must therefore examine cross-market effects.

For example:

More users → more creators → more content → more engagement → more advertisers → more revenue → more investment → more users

This feedback mechanism can substantially increase barriers to entry.

10. Competition Concerns Created by Concentration

10.1 Self-preferencing

A platform may give preferential treatment to its own:

• content;
• applications;
• advertising services;
• search results;
• payment systems; or
• recommendation products.

10.2 Data advantage

A dominant platform may possess behavioural information unavailable to rivals.

This may create:

Data advantage → better targeting → better recommendations → greater engagement → additional data

10.3 Switching costs

Users may find it difficult to leave because they would lose:

• followers;
• social connections;
• historical content;
• playlists;
• reputation;
• creator audiences;
• accumulated data; or
• platform-specific digital assets.

10.4 Multi-homing restrictions

Competition may be weakened if users, creators or advertisers are discouraged from participating on rival platforms.

This can be achieved through:

• contractual exclusivity;
• technical restrictions;
• discriminatory ranking;
• API restrictions;
• account limitations; or
• financial penalties.

10.5 Killer acquisitions

A dominant platform may acquire an emerging engagement platform before it becomes a meaningful competitor.

The competition question becomes:

Would the acquired platform have developed into a significant competitive constraint?

This makes merger review particularly important.

11. Essential-Facility and Interoperability Issues

In certain circumstances, a dominant engagement platform may control an infrastructure that competitors need to compete effectively.

Potential examples include:

• social-graph portability;
• messaging interoperability;
• authentication;
• API access;
• creator analytics;
• advertising measurement;
• interoperability with complementary applications.

A refusal to provide access is not automatically unlawful. Competition law generally requires careful analysis of:

1. dominance;
2. indispensability;
3. exclusionary effect;
4. objective justification;
5. feasibility of access; and
6. effect on consumer welfare.

12. Merger-Control Concerns

Traditional turnover thresholds can fail to capture acquisitions of highly valuable digital startups.

A large platform could acquire:

• a recommendation startup;
• AI engagement technology;
• a social-media application;
• a creator platform;
• an attention-measurement business; or
• a behavioural-data company.

The acquisition might eliminate a future competitive constraint even where the target has little current revenue.

Therefore modern merger policy increasingly considers:

• potential competition;
• innovation;
• data assets;
• network effects;
• ecosystem expansion; and
• nascent competition.

13. Consumer Welfare Issues

Cognitive engagement platforms complicate the conventional price-centred consumer-welfare model.

A service can be free while competition problems manifest through:

• reduced privacy;
• excessive data extraction;
• reduced choice;
• reduced innovation;
• lower-quality recommendations;
• increased advertising intensity;
• reduced interoperability; or
• diminished control over personal data.

Therefore, quality, privacy, innovation and choice may complement price-based analysis.

14. Remedies

Competition authorities can consider several remedies.

Structural remedies

• divestiture;
• prohibition of acquisitions;
• separation of business units.

Behavioural remedies

• non-discrimination;
• interoperability;
• data portability;
• restrictions on self-preferencing;
• transparent ranking;
• access obligations.

Data remedies

• data silos;
• consent requirements;
• restrictions on cross-service combination;
• portability.

Platform remedies

• multi-homing;
• API access;
• switching mechanisms;
• interoperability.

The EU DMA illustrates the movement toward ex-ante obligations, while Germany's Section 19a framework provides enhanced abuse control for major digital ecosystems.

15. China-Specific Perspective

China's Anti-Monopoly Law has become increasingly important for platform ecosystems.

Relevant issues include:

• platform exclusivity;
• algorithmic discrimination;
• data advantages;
• excessive platform power;
• self-preferencing;
• tying;
• interoperability;
• platform mergers;
• abuse of dominance.

The Alibaba enforcement action and the Tencent litigation illustrate that Chinese competition law increasingly recognises the special characteristics of Internet-platform markets.

China's approach is particularly significant because platform competition can involve both economic network effects and control over digital ecosystems.

16. Comparative Legal Position

17. Key Legal Principles Emerging from the Case Law

The six principal cases collectively demonstrate several important principles:

Principle 1 — Engagement can be an economic asset

Control over user attention can translate into advertising, data and ecosystem power.

Principle 2 — Data can reinforce dominance

Large-scale data accumulation can create advantages that competitors cannot easily replicate.

Principle 3 — Algorithms can affect competitive conditions

Ranking and recommendation systems can determine which businesses receive access to user attention.

Principle 4 — Ecosystems must sometimes be examined across markets

Power may derive from the combination of several interconnected services rather than from one isolated product.

Principle 5 — Exclusivity can be especially problematic in platform markets

Where users and merchants cannot effectively multi-home, exclusionary effects may be amplified.

Principle 6 — Potential competition matters

A small engagement platform can represent an important future competitive constraint even if its present market share is modest.

18. Conclusion

Cognitive engagement platform concentration represents a modern competition-law problem in which the relevant source of power is not merely price or conventional market share, but the combination of attention, data, algorithms, network effects, creators, advertisers and ecosystem control.

The cases involving Meta/Facebook, Google Shopping, Google Android, Facebook data processing, Tencent and Alibaba demonstrate different dimensions of this problem.

The central analytical framework should therefore examine:

Market definition → user engagement → network effects → data accumulation → algorithmic control → ecosystem leverage → exclusionary conduct → barriers to entry → innovation → consumer choice → appropriate remedies.