Evidence map›Paper›PMID 39242855›Full record

ArticleCommunications psychology2024

The Russian war in Ukraine increased Ukrainian language use on social media.

Daniel Racek, Brittany I Davidson, Paul W Thurner, Xiao Xiang Zhu, Göran Kauermann

Abstract read
In one paragraph

Article in Communications psychology, 2024. 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
–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

2 citing papers in PubMed.

  1. Review
  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

5 authors.

Daniel RacekInstitute of Statistics, Ludwig-Maximilians-University Munich, Munich, Germany. daniel.racek@stat.uni-muenchen.de.ORCID http://orcid.org/0000-0002-9564-7880
Brittany I DavidsonSchool of Management, University of Bath, Bath, UK.ORCID http://orcid.org/0000-0001-9886-9043
Paul W ThurnerInstitute of Political Science, Ludwig-Maximilians-University Munich, Munich, Germany.ORCID http://orcid.org/0000-0001-7336-9878
Xiao Xiang ZhuSchool of Engineering and Design, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0001-5530-3613
Göran KauermannInstitute of Statistics, Ludwig-Maximilians-University Munich, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of language is innately political, often a vehicle of cultural identity and the basis for nation building. Here, we examine language choice and tweeting activity of Ukrainian citizens based on 4,453,341 geo-tagged tweets from 62,712 users before and during the Russian war in Ukraine, from January 2020 to October 2022. Using statistical models, we disentangle sample effects, arising from the in- and outflux of users on Twitter (now X), from behavioural effects, arising from behavioural changes of the users. We observe a steady shift from the Russian language towards Ukrainian already before the war, which drastically speeds up with its outbreak. We attribute these shifts in large part to users' behavioural changes. Notably, our analysis shows that more than half of the Russian-tweeting users switch towards Ukrainian with the Russian invasion. We interpret these findings as users' conscious choice towards a more Ukrainian (online) identity and self-definition of being Ukrainian.

Identifiers

PMID39242855
PMCPMC11332000

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.