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Causal evidence for social group sizes from Wikipedia editing data.
1ChiTek-i AS, Oslo, Norway.
Royal Society Open Science
|October 3, 2024
Summary
Human communities exhibit self-organization, with Wikipedia editing groups forming around two specific sizes: ~50 for high contention and ~150 for regular teams. These findings support social network theories and have implications for online platform governance.
Area of Science:
- Social Network Analysis
- Computational Social Science
- Human Behavior
Background:
- Human communities display self-organizing properties.
- Dunbar's Number suggests cognitive limits on social relationships.
- Online platforms like Wikipedia involve spontaneous group formation.
Purpose of the Study:
- To analyze Wikipedia editing histories to identify emergent group sizes.
- To investigate the self-organizing principles in human online communities.
- To explore the implications for online platform governance and security.
Main Methods:
- Analysis of Wikipedia editing histories across diverse subject pages.
- Statistical analysis to identify peaks in transient group sizes.
- Application of a bipartite trust model to derive a scaling law.
Main Results:
- Identified two emergent peaks in transient group sizes: approximately 50 (maximal contention) and 150 (regular team).
- Observed group sizes are consistent with conversational group sizes and Dunbar graph structures.
- Derived a scaling law fitting the data, applicable to seeded group attraction processes.
Conclusions:
- Spontaneous online communities of strangers demonstrate self-organizing properties.
- Findings provide evidence for Dunbar Numbers in digital social structures.
- Results have significant implications for Wikipedia governance and online social platform security.
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