Evidence map›Paper›PMID 41911288›Full record

ArticlePloS one2026

Activity constraints and the emergence of non-scale-free networks: Evidence from hip-hop and academia.

Jaemin Lee, Yujie Li

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Jaemin LeeDepartment of Sociology, The Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong SAR, Hong Kong, China.ORCID https://orcid.org/0000-0002-4720-6597
Yujie LiDivision of Computational Social Science, The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Power-law distributions are widely used to characterize complex networks, yet recent work shows that scale-freeness is far less universal than once assumed, especially in social networks. We propose activity constraints-the finite time and effort required to complete collaborative ties-as a mechanism that limits hub growth and produces non-scale-free degree distributions. Using synthetic models and mathematical derivations, we show that imposing capacity limits on high-quality actors shifts degree distributions away from power laws and toward log-normal forms. We then examine degree saturation in two empirical settings: hip-hop featuring networks and academic coauthorship networks. In both cases, high-quality actors receive more ties, but their realized degree saturates relative to expectations, yielding sublinear or S-shaped quality-degree relationships. These findings demonstrate how micro-level workload constraints generate macro-level deviations from scale-free structure and highlight the importance of distinguishing activity-intensive from low-cost tie-formation processes when evaluating claims of scale-freeness in networks.

Indexed as

Models, TheoreticalSocial NetworkingAcademiaHumans

Identifiers

PMID41911288
PMCPMC13035169

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.