Like and Follower Counts is public metrics tie self-worth to engagement, training behavior toward what performs. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0170, within the Social Perverse Pattern family. The core principle: public metrics tie self-worth to engagement, training behavior toward what performs. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
Scientific Definition
Public metrics tie self-worth to engagement, training behavior toward what performs.
Plain-English Definition
Public metrics tie self-worth to engagement, training behavior toward what performs.
Feynman Explanation
Your self-image now lives in a chart.
Core Principle
Public metrics tie self-worth to engagement, training behavior toward what performs.
Mechanisms
Pending editorial review.
Public metrics tie self-worth to engagement, training behavior toward what performs.
Pending editorial review.
Pending editorial review.
Default visibility of metrics shapes user identity.
Pending editorial review.
Pending editorial review.
Inputs (Triggers)
Pending editorial review.
Outputs (Behaviors)
Pending editorial review.
Behavioral Signature
Your self-image now lives in a chart.
Examples
- Documented mental-health impacts of public counts.
- Default visibility of metrics shapes user identity.
Pending editorial review.
Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.
Why this element matters to incentive design
Executives usually notice this element only after it has cost something. By then it looks like a one-off. It is not. The mechanism underneath it is straightforward: public metrics tie self-worth to engagement, training behavior toward what performs. You can recognize it in the field by its signature: your self-image now lives in a chart. Every element in the Incentives dimension changes the perceived payoff of an action before the action happens, which is exactly where incentive design has leverage.
How it gets exploited
Left undesigned, default visibility of metrics shapes user identity. It is amplified whenever default visibility of metrics shapes user identity. Inside organizations that shows up as default visibility of metrics shapes user identity. The pattern is the same one Goodhart's Law describes: the measurable proxy attracts the effort, and the purpose behind it quietly loses funding.
How the Lab designs around it
The redesign move is to hide counts by default. Private engagement modes. Watch for it at the boundaries: handoffs, promotions, incident reviews, and budget cycles are where this element gets its power.
Famous Experiments
Pending editorial review.
Design Principles
- Hide counts by default. Private engagement modes.
Measurement Approaches
Pending editorial review.
Evidence
Pending editorial review.
Pending editorial review.
The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Hide counts by default. Private engagement modes.
Pending editorial review.
Pending editorial review.
Interactive Mini Network
Click any neighbor to re-center the graph and follow the threads of connection.
Knowledge Graph Neighbors
Auto-linked to the rest of the Human Behavior Taxonomy by family, domain, dimension, and shared keywords.
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Region-average rent subsidies inadvertently fund consolidation of poverty into resource-poor cores.
Celebrating overwork normalizes burnout and crowds out rest, family, and craft.
Tribal identity markers reward in-group loyalty over coalition-building.
Audience attention rewards alarming framings, distorting perception of risk.
Optimizing tools and systems can become a sophisticated form of avoiding hard work.
Funding rules force districts to add sugary sides to hit caloric minimums.
Discount framing nudges people to buy things they wouldn't otherwise want.
Where Like and Follower Counts is cited in the corpus
Essays, field guides, and diagnostics from The Incentives Lab that apply this element.
- Field guideIncentives: definition, types, examples
The parent field guide for this element.
- ReferenceThe laws of incentives
Goodhart, Campbell, and the Cobra Effect.
- EssayThe Perverse Incentives Hiding in Your KPIs
The measurement failure mode for this element.
- EssayWhy Government Transformation Stalls
The public-sector version of this pattern.
- CourseIncentives 101
The free ten-part primer on reading a payoff structure.
- ReferenceThe Periodic Table of Human Behavior
The full 1,267-element map this page belongs to.
Questions about Like and Follower Counts
- What is Like and Follower Counts?
- Like and Follower Counts is public metrics tie self-worth to engagement, training behavior toward what performs. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0170, within the Social Perverse Pattern family. The core principle: public metrics tie self-worth to engagement, training behavior toward what performs. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
- What is an example of Like and Follower Counts?
- Default visibility of metrics shapes user identity. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-INC-0170).
- How is Like and Follower Counts exploited?
- Default visibility of metrics shapes user identity.
- How do you design around Like and Follower Counts?
- Hide counts by default. Private engagement modes.
- Which behavioral dimension does Like and Follower Counts belong to?
- Like and Follower Counts is classified in the Incentives dimension (INC) of the Human Behavior Taxonomy™, family "Social Perverse Pattern", class "Perverse Incentive". Its permanent identifier is HBT-INC-0170 and its evidence grade is C.