The Emperor's Dilemma
A Computational Model of Self-Enforcing Norms
Bibliographic Data
| ID | 2215980 |
|---|---|
| Authors | Damon Centola (0000-0002-8084-2333, Cornell University), R Willer (0000-0003-3404-6472, Cornell University), Michael W Macy (0000-0003-0024-5027, Cornell University), Michael Macy |
| Year | 2005 |
| Volume | 110 |
| Issue | 4 |
| Pages | 1009-1040 |
| Publication date | 2005-01-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | American Journal of Sociology (JOURNAL) |
| Journal identifiers | ISSN: 0002-9602 • E-ISSN: 1537-5390 |
| Publisher | University of Chicago Press (PUBLISHER • US) |
| DOI | 10.1086/427321 |
| OpenAlex | W2046190965 |
| Language | EN |
| Citations received | 127 |
| References cited | 55 |
The authors demonstrate the uses of agent‐based computational models in an application to a social enigma they call the “emperor’s dilemma,” based on the Hans Christian Andersen fable. In this model, agents must decide whether to comply with and enforce a norm that is supported by a few fanatics and opposed by the vast majority. They find that cascades of self‐reinforcing support for a highly unpopular norm cannot occur in a fully connected social network. However, if agents’ horizons are limited to immediate neighbors, highly unpopular norms can emerge locally and then spread. One might expect these cascades to be more likely as the number of “true believers” increases, and bridge ties are created between otherwise distant actors. Surprisingly, the authors observed quite the opposite effects
Bridge (graph theory · Computer security · Dilemma · Emperor · Epistemology · Law and economics · Norm (philosophy · Political science · Social dilemma · Sociology · Computer Science · Evolutionary Game Theory and Cooperation · Game Theory and Applications · History · Law · Medicine · Opinion Dynamics and Social Influence · Philosophy · Psychology · Social Psychology
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| Unique citing works | 127 |
|---|---|
| Citations per year | 6,68 |
| Citation span | 2007 - 2026 (20) |
| Citation velocity | current |
| Highly cited | Yes |
| Citation types | Neutral: 126 |