Evidence map›Paper›PMID 38212630›Full record

ArticleScientific reports2024

Partisan styles of self-presentation in U.S. Twitter bios.

Liam Essig, Daniel DellaPosta

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Liam EssigDepartment of Sociology and Criminology, Pennsylvania State University, University Park, PA, 16802, USA. lwe5065@psu.edu.
Daniel DellaPostaDepartment of Sociology and Criminology, Pennsylvania State University, University Park, PA, 16802, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Political polarization in the United States goes beyond divided opinions on key political issues, extending to realms of culture, lifestyle, and social identity once thought to be apolitical. Using a sample of 1 million Twitter bios, this study investigates how users' partisan self-presentation on social media tends to include cultural as well as political markers. Representing the text in Twitter bios as semantic networks, the study reveals clear partisan differences in how users describe themselves, even on topics that seem apolitical. Consequently, active Twitter users' political alignments can be statistically inferred from the non-political references in their bios, even in the absence of explicitly partisan language. These findings offer further evidence of partisan polarization that is aligned with lifestyle preferences. Further research is needed to determine if users are aware of that alignment, which might indicate the politicization of lifestyle preferences. The findings also suggest an under-recognized way social media can promote polarization, not through political discourse or argument, but simply in how users present cultural and lifestyle preferences on those platforms.

Indexed as

Social MediaAttitudeHumansLanguageLife StylePoliticsUnited States

Identifiers

PMID38212630
PMCPMC10784547

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.