Evidence map›Paper›PMID 36105923›Full record

ArticleSocial network analysis and mining2022

Cross-platform information spread during the January 6th capitol riots.

Lynnette Hui Xian Ng, Iain J Cruickshank, Kathleen M Carley

Abstract read
In one paragraph

Article in Social network analysis and mining, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

3 authors.

Lynnette Hui Xian NgCenter for Computational Analysis of Social and Organizational Systems, Carnegie Mellon University, 4665 Forbes Avenue, Pittsburgh, PA 15213 USA.ORCID 0000-0002-2740-7818
Iain J Cruickshank *Center for Computational Analysis of Social and Organizational Systems, Carnegie Mellon University, 4665 Forbes Avenue, Pittsburgh, PA 15213 USA.
Kathleen M Carley *Center for Computational Analysis of Social and Organizational Systems, Carnegie Mellon University, 4665 Forbes Avenue, Pittsburgh, PA 15213 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Social media has become an integral component of the modern information system. An average person typically has multiple accounts across different platforms. At the same time, the rise of social media facilitates the spread of online mis/disinformation narratives within and across these platforms. In this study, we characterize the coordinated information dissemination of information laden with mis- and disinformation narratives within and across two platforms, Parler and Twitter, during the online discourse surrounding the January 6th 2021 Capitol Riots event. Through the use of username similarity, we discover joint theme endorsements between both platforms. Using anomalously high volume of shared-link matches of external websites and YouTube videos, we discover separate information consumption habits between both platforms, with very few common sources of information between users of the different platforms. However, through analyzing the similarity of the texts with Locality Sensitive Hashing of constructed text vectors, we identify similar narratives between the platforms despite separate consumption of external websites, highlighting the similarities and differences of information spread within and between the two social media environments.

Indexed as

Coordinated information disseminationNatural language processingParlerSocial media coordinationTwitter

Identifiers

PMID36105923
PMCPMC9461432

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.