Evidence map›Paper›PMID 37850669›Full record

ReviewTopics in cognitive science2026

Understanding Collective Human Behavior in Social Media Networks Via the Dynamical Hypothesis: Applications to Radicalization and Conspiratorial Beliefs.

Aaron Necaise, Jingjing Han, Hana Vrzáková, Mary Jean Amon

Open access · bronzeAbstract readReview
In one paragraph

Review in Topics in cognitive science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 45% of its field
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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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 at 3 institutions in 5 countries.

Aaron NecaiseSchool of Modeling, Simulation, and Training, University of Central Florida.
Jingjing HanSchool of Journalism, Fudan University.
Hana VrzákováSchool of Computing, University of Eastern Finland.
Mary Jean AmonSchool of Modeling, Simulation, and Training, University of Central Florida.
University of Central Florida · USFudan University · CNUniversity of Eastern Finland · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The dynamical hypothesis has served to explore the ways in which cognitive agents can be understood dynamically and considered dynamical systems. Originally used to explain simple physical systems as a metaphor for cognition (i.e., the Watt governor) and eventually more complex animal systems (e.g., bird flocks), we argue that the dynamical hypothesis is among the most viable approaches to understanding pressing modern-day issues that arise from collective human behavior in online social networks. First, we discuss how the dynamical hypothesis is positioned to describe, predict, and explain the time-evolving nature of complex systems. Next, we adopt an interdisciplinary perspective to describe how online social networks are appropriately understood as dynamical systems. We introduce a dynamical modeling approach to reveal information about emergent properties in social media, where radicalized conspiratorial beliefs arise via coordination between user-level and community-level comments. Lastly, we contrast how the dynamical hypothesis differs from alternatives in explaining collective human behavior in social networks.

Indexed as

Social BehaviorSocial MediaSocial NetworkingGroup DynamicsHumansSocial GroupComplex systemsCoordinationDynamical hypothesisRadicalizationSentimentSocial networksWavelet analysis

Identifiers

PMID37850669
PMCPMC13397063
OpenAlexW4387729251

What OpenQuestion holds

Textmetadata
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.