Social network structure scales with group size in a multi-species analysis
Bibliographic record
Abstract
Abstract Social networks can shape the evolution and transmission of behaviours. Recent studies have characterized social networks within species, but we know relatively little about the drivers of variation in the structure of social networks across species. Here, we analyze a database of 631 social networks from more than 30 animal species to test how social network properties scale with group size. We examine three properties of social network topology: the uniformity of edge weights within the group, the selectivity of individuals for particular social partners, and the amount of heterogeneity among individuals in social behaviour. We show that most of the variation in these three network properties is due to differences between focal species and/or study methodologies, with only negligible differences between the three animal classes in our analysis (birds, mammals, and insects). Our analysis also indicates that group size is the key factor that determines the topology of animal social networks. In smaller groups, edge weights are distributed more uniformly, and individuals show greater selectivity regarding their social partners. These results suggest that there are general scaling rules governing the social networks of diverse animal species. In small groups, individuals form strong connections to a selective set of partners, whereas in large groups, weaker ties are common, and individuals are less likely to limit their interactions to specific partners. Significance Statement Sociality is observed throughout the animal kingdom. Animal societies also vary widely in group size, from a few individuals to groups with millions on individuals. How do animal social networks vary across this spectrum? We investigated this question using data compiled from recent bird, mammal, and insect studies. Surprisingly, we found broad overlap in the social network structures of these three distinct animal classes. We tested the effect of group size on social network structure, and found that in small groups, individuals form stronger social ties with preferred social partners; by contrast, animals in large groups have weaker and less selective social ties. These results suggest that diverse animal groups are governed by similar processes that determine the structure of their social networks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".