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Empirical social triad statistics can be explained with dyadic homophylic interactions.
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- Author(s): Pham TM;Pham TM;Pham TM; Korbel J; Korbel J; Korbel J; Hanel R; Hanel R; Hanel R; Thurner S; Thurner S; Thurner S; Thurner S; Thurner S
- Source:
Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2022 Feb 08; Vol. 119 (6).- Publication Type:
Journal Article; Research Support, Non-U.S. Gov't- Language:
English - Source:
- Additional Information
- Source: Publisher: National Academy of Sciences Country of Publication: United States NLM ID: 7505876 Publication Model: Print Cited Medium: Internet ISSN: 1091-6490 (Electronic) Linking ISSN: 00278424 NLM ISO Abbreviation: Proc Natl Acad Sci U S A Subsets: MEDLINE
- Publication Information: Original Publication: Washington, DC : National Academy of Sciences
- Subject Terms:
- Abstract: The remarkable robustness of many social systems has been associated with a peculiar triangular structure in the underlying social networks. Triples of people that have three positive relations (e.g., friendship) between each other are strongly overrepresented. Triples with two negative relations (e.g., enmity) and one positive relation are also overrepresented, and triples with one or three negative relations are drastically suppressed. For almost a century, the mechanism behind these very specific ("balanced") triad statistics remained elusive. Here, we propose a simple realistic adaptive network model, where agents tend to minimize social tension that arises from dyadic interactions. Both opinions of agents and their signed links (positive or negative relations) are updated in the dynamics. The key aspect of the model resides in the fact that agents only need information about their local neighbors in the network and do not require (often unrealistic) higher-order network information for their relation and opinion updates. We demonstrate the quality of the model on detailed temporal relation data of a society of thousands of players of a massive multiplayer online game where we can observe triangle formation directly. It not only successfully predicts the distribution of triangle types but also explains empirical group size distributions, which are essential for social cohesion. We discuss the details of the phase diagrams behind the model and their parameter dependence, and we comment on to what extent the results might apply universally in societies.
Competing Interests: The authors declare no competing interest.
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Phys Rev E. 2021 Aug;104(2-1):024307. (PMID: 34525606) - Contributed Indexing: Keywords: signed networks; social balance; social stability
- Publication Date: Date Created: 20220202 Date Completed: 20220307 Latest Revision: 20220307
- Publication Date: 20221213
- Accession Number: PMC8833205
- Accession Number: 10.1073/pnas.2121103119
- Accession Number: 35105814
- Source:
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