Abstract
Semantic priming has been studied for nearly 50 years across various experimental manipulations and theoretical frameworks. Although previous studies provide insight into the cognitive underpinnings of semantic representations, they have suffered from small sample sizes and a lack of linguistic and cultural diversity. In this Registered Report, we measured the size and the variability of the semantic priming effect across 19 languages (n = 25,163 participants analysed) by creating the largest available database of semantic priming values using an adaptive sampling procedure. We found evidence for semantic priming in terms of differences in response latencies between related word-pair conditions and unrelated word-pair conditions. Model comparisons showed that the inclusion of a random intercept for language improved model fit, providing support for variability in semantic priming across languages. This study highlights the robustness and variability of semantic priming across languages and provides a rich, linguistically diverse dataset for further analysis. The Stage 1 protocol for this Registered Report was accepted in principle on 15 July 2022. The protocol, as accepted by the journal, can be found at https://osf.io/u5bp6 (registration) or https://osf.io/q4fjy (preprint version 6, 31 May 2022).
| Original language | English |
|---|---|
| Pages (from-to) | 182-201 |
| Number of pages | 20 |
| Journal | Nature Human Behaviour |
| Volume | 10 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2026 |
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In: Nature Human Behaviour, Vol. 10, No. 1, 01.2026, p. 182-201.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Measuring the semantic priming effect across many languages
AU - Buchanan, Erin M.
AU - Cuccolo, Kelly
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AU - Giannouli, Vaitsa
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AU - Ihaya, Keiko
AU - Ilczuk, Ewa
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AU - Kratochvil, Tomas
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AU - Körtvélyessy, Lívia
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AU - Kękuś, Magdalena
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AU - Stephen, Ian D.
AU - Stevens, Laura M.
AU - Stewart, Suzanne L.K.
AU - Steyrl, David
AU - Stieger, Stefan
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AU - Suarez, Mar
AU - Szala, Anna
AU - Szmalec, Arnaud
AU - Sznycer, Daniel
AU - Szumowska, Ewa
AU - Söylemez, Sinem
AU - Söylemez, Bahadır
AU - Takashima, Kaito
AU - Tamnes, Christian K.
AU - Tan, Joel C.R.
AU - Tang, Chengxiang
AU - Tavel, Peter
AU - Tejada, Julian
AU - Thompson, Benjamin C.
AU - Tiernan, Jake G.
AU - Torres-Muñoz, Vicente
AU - Touloumakos, Anna K.
AU - Trémolière, Bastien
AU - Tschense, Monika
AU - Türkan, Belgüzar Nilay
AU - Vadillo, Miguel A.
AU - Vannucci, Caterina
AU - Varnum, Michael E.W.
AU - Vasilev, Martin R.
AU - Vaughn, Leigh Ann
AU - Verkampt, Fanny
AU - Villar, Liliana M.
AU - Wallot, Sebastian
AU - Wang, Lijun
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AU - Williams, Glenn Patrick
AU - Willinger, David
AU - Wolfe, Kelly
AU - Wormley, Alexandra S.
AU - Yamada, Yuki
AU - Yang, Yunkai
AU - Zhou, Yuwei
AU - Zhang, Mengfan
AU - Zheng, Wang
AU - Zheng, Yueyuan
AU - Zhou, Chenghao
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AU - Çoker, Ogeday
AU - Çoksan, Sami
AU - Öner, Sezin
AU - Özdoğru, Asil Ali
AU - Şahin, Seda Merve
AU - Kasanov, Dauren
AU - Arvanitis, Alexios
AU - Brick, Cameron
AU - Colloff, Melissa F.
AU - Gallyamova, Albina
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AU - Zhou, Xingxing
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N1 - Publisher Copyright: © The Author(s), under exclusive licence to Springer Nature Limited 2025.
PY - 2026/1
Y1 - 2026/1
N2 - Semantic priming has been studied for nearly 50 years across various experimental manipulations and theoretical frameworks. Although previous studies provide insight into the cognitive underpinnings of semantic representations, they have suffered from small sample sizes and a lack of linguistic and cultural diversity. In this Registered Report, we measured the size and the variability of the semantic priming effect across 19 languages (n = 25,163 participants analysed) by creating the largest available database of semantic priming values using an adaptive sampling procedure. We found evidence for semantic priming in terms of differences in response latencies between related word-pair conditions and unrelated word-pair conditions. Model comparisons showed that the inclusion of a random intercept for language improved model fit, providing support for variability in semantic priming across languages. This study highlights the robustness and variability of semantic priming across languages and provides a rich, linguistically diverse dataset for further analysis. The Stage 1 protocol for this Registered Report was accepted in principle on 15 July 2022. The protocol, as accepted by the journal, can be found at https://osf.io/u5bp6 (registration) or https://osf.io/q4fjy (preprint version 6, 31 May 2022).
AB - Semantic priming has been studied for nearly 50 years across various experimental manipulations and theoretical frameworks. Although previous studies provide insight into the cognitive underpinnings of semantic representations, they have suffered from small sample sizes and a lack of linguistic and cultural diversity. In this Registered Report, we measured the size and the variability of the semantic priming effect across 19 languages (n = 25,163 participants analysed) by creating the largest available database of semantic priming values using an adaptive sampling procedure. We found evidence for semantic priming in terms of differences in response latencies between related word-pair conditions and unrelated word-pair conditions. Model comparisons showed that the inclusion of a random intercept for language improved model fit, providing support for variability in semantic priming across languages. This study highlights the robustness and variability of semantic priming across languages and provides a rich, linguistically diverse dataset for further analysis. The Stage 1 protocol for this Registered Report was accepted in principle on 15 July 2022. The protocol, as accepted by the journal, can be found at https://osf.io/u5bp6 (registration) or https://osf.io/q4fjy (preprint version 6, 31 May 2022).
UR - https://www.scopus.com/pages/publications/105017844574
UR - https://www.scopus.com/pages/publications/105017844574#tab=citedBy
U2 - 10.1038/s41562-025-02254-x
DO - 10.1038/s41562-025-02254-x
M3 - Article
C2 - 40993402
AN - SCOPUS:105017844574
VL - 10
SP - 182
EP - 201
JO - Nature Human Behaviour
JF - Nature Human Behaviour
IS - 1
ER -