Evidence map›Paper›PMID 40051436›Full record

ArticleNpj complexity2025

Distinguishing mechanisms of social contagion from local network view.

Elsa Andres, Gergely Ódor, Iacopo Iacopini, Márton Karsai

Abstract read
In one paragraph

Article in Npj complexity, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Elsa AndresDepartment of Network and Data Science, Central European University, Vienna, 1100 Austria.
Gergely ÓdorDepartment of Network and Data Science, Central European University, Vienna, 1100 Austria.
Iacopo IacopiniNetwork Science Institute, Northeastern University London, London, E1W 1LP UK.
Márton KarsaiDepartment of Network and Data Science, Central European University, Vienna, 1100 Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The adoption of individual behavioural patterns is largely determined by stimuli arriving from peers via social interactions or from external sources. Based on these influences, individuals are commonly assumed to follow simple or complex adoption rules, inducing social contagion processes. In reality, multiple adoption rules may coexist even within the same social contagion process, introducing additional complexity to the spreading phenomena. Our goal is to understand whether coexisting adoption mechanisms can be distinguished from a microscopic view at the egocentric network level without requiring global information about the underlying network, or the unfolding spreading process. We formulate this question as a classification problem, and study it through a likelihood approach and with random forest classifiers in various synthetic and data-driven experiments. This study offers a novel perspective on the observations of propagation processes at the egocentric level and a better understanding of landmark contagion mechanisms from a local view.

Indexed as

Complex networksComputational scienceScientific data

Identifiers

PMID40051436
PMCPMC11879858

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.