Evidence map›Paper›PMID 35288567›Full record

ArticleNature communications2022

Universality, criticality and complexity of information propagation in social media.

Daniele Notarmuzi, Claudio Castellano, Alessandro Flammini, Dario Mazzilli, Filippo Radicchi

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
4.7field-weighted citation impact, top 4% 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

10 citing papers in PubMed, 42 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Rumor propagation on hypergraphs.Nature communications · 2026
    Article
  5. Article
  6. Article
  7. Collective dynamics behind success.Nature communications · 2024
    Review
  8. Article
  9. Article
  10. 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

5 authors at 2 institutions in 2 countries.

Daniele NotarmuziCenter for Complex Networks and Systems Research, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47408, USA.ORCID http://orcid.org/0000-0001-5565-3971
Claudio CastellanoIstituto dei Sistemi Complessi (ISC-CNR), Via dei Taurini 19, I-00185, Roma, Italy.ORCID http://orcid.org/0000-0002-3773-3801
Alessandro FlamminiCenter for Complex Networks and Systems Research, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47408, USA.
Dario MazzilliCenter for Complex Networks and Systems Research, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47408, USA.ORCID http://orcid.org/0000-0001-7948-7584
Filippo RadicchiCenter for Complex Networks and Systems Research, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47408, USA. filiradi@indiana.edu.ORCID http://orcid.org/0000-0002-8352-1287
Indiana University Bloomington · USCentro Ricerche Enrico Fermi · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Statistical laws of information avalanches in social media appear, at least according to existing empirical studies, not robust across systems. As a consequence, radically different processes may represent plausible driving mechanisms for information propagation. Here, we analyze almost one billion time-stamped events collected from several online platforms - including Telegram, Twitter and Weibo - over observation windows longer than ten years, and show that the propagation of information in social media is a universal and critical process. Universality arises from the observation of identical macroscopic patterns across platforms, irrespective of the details of the specific system at hand. Critical behavior is deduced from the power-law distributions, and corresponding hyperscaling relations, characterizing size and duration of avalanches of information. Statistical testing on our data indicates that a mixture of simple and complex contagion characterizes the propagation of information in social media. Data suggest that the complexity of the process is correlated with the semantic content of the information that is propagated.

Indexed as

Social MediaHumans

Identifiers

PMID35288567
PMCPMC8921196
OpenAlexW3197521018

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.