Evidence map›Paper›PMID 40379774›Full record

ArticleScientific reports2025

Using the Language of elite athletes to predict their personality and on court transgressions.

Maor Daniel Levitin, Itamar Zan Ger, Ze'ev Sovik, Ariel Taieb, Lyle Ungar, Michael Gilead

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

6 authors.

Maor Daniel LevitinTel-Aviv University, P.O.B. 39040, Tel Aviv, 6997801, Israel. maorlevitin@gmail.com.ORCID http://orcid.org/0009-0006-9926-5501
Itamar Zan GerBen-Gurion University of the Negev, P.O.B. 653, Beer-Sheva, 8410501, Israel.
Ze'ev SovikTel-Aviv University, P.O.B. 39040, Tel Aviv, 6997801, Israel.
Ariel TaiebTel-Aviv University, P.O.B. 39040, Tel Aviv, 6997801, Israel.
Lyle UngarUniversity of Pennsylvania, 504 Levine, 3330 Walnut St., Philadelphia, PA, 19104-6309, USA.
Michael GileadTel-Aviv University, P.O.B. 39040, Tel Aviv, 6997801, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Personality is predictive of many behaviors, but personality questionnaires cannot be readily administered to persons of interest. The language people use to express themselves can often predict personality and so should, in theory, provide a surrogate marker for predicting behavior. We used social media (Twitter) language from a sample of 252 NBA players to estimate their Five Factor personality scores, and then, used these scores to try and predict on-court transgressive behavior. A machine learning model was able to predict players' tendency to commit technical fouls (predictive performance: r = .18); with the most important contributors to the model including neuroticism, extraversion, and conscientiousness. These findings show that personality can predict individual choices and behaviors in specific contexts; furthermore, by assessing the degree to which our digital footprint can be used to derive actionable predictions of behavior, the current findings could inform discussions concerning regulations of data privacy.

Indexed as

AthletesLanguagePersonalityAdultFemaleHumansMachine LearningMaleSocial MediaSurveys and QuestionnairesYoung Adult

Identifiers

PMID40379774
PMCPMC12084345

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.