dc.contributor.author | Stein, Roni | |
dc.contributor.author | Frost, Ram | |
dc.contributor.author | Siegelman, Noam | |
dc.date.accessioned | 2025-02-19T16:22:26Z | |
dc.date.available | 2025-02-19T16:22:26Z | |
dc.date.issued | 2024 | |
dc.identifier.citation | Stein, R., Frost, R. & Siegelman, N. HeLP: The Hebrew Lexicon project. Behav Res 56, 8761–8783 (2024). https://doi.org/10.3758/s13428-024-02502-4 | es_ES |
dc.identifier.citation | Behavior Research Methods | |
dc.identifier.issn | 1554-351X | |
dc.identifier.uri | http://hdl.handle.net/10810/72835 | |
dc.description | Published on 9 September 2024 | es_ES |
dc.description.abstract | Lexicon projects (LPs) are large-scale data resources in different languages that present behavioral results from visual word recognition tasks. Analyses using LP data in multiple languages provide evidence regarding cross-linguistic differences as well as similarities in visual word recognition. Here we present the first LP in a Semitic language—the Hebrew Lexicon Project (HeLP). HeLP assembled lexical decision (LD) responses to 10,000 Hebrew words and nonwords, and naming responses to a subset of 5000 Hebrew words. We used the large-scale HeLP data to estimate the impact of general predictors (lexicality, frequency, word length, orthographic neighborhood density), and Hebrew-specific predictors (Semitic structure, presence of clitics, phonological entropy) of visual word recognition performance. Our results revealed the typical effects of lexicality and frequency obtained in many languages, but more complex impact of word length and neighborhood density. Considering Hebrew-specific characteristics, HeLP data revealed better recognition of words with a Semitic structure than words that do not conform to it, and a drop in performance for words comprising clitics. These effects varied, however, across LD and naming tasks. Lastly, a significant inhibitory effect of phonological ambiguity was found in both naming and LD. The implications of these findings for understanding reading in a Semitic language are discussed. | es_ES |
dc.description.sponsorship | Work in this paper was supported by the following funding sources: the European Research Council (ERC) Advanced Grant, project 692502-L2STAT, under the Horizon 2020 research and innovation program (awarded to RF); the Israel Science Foundation (ISF) Grant, project 705/20 (awarded to RF); the Israel Science Foundation (ISF) Grant, project 1034/23 (awarded to NS); and an Azrieli Early Career Faculty Fellowship (awarded to NS). We thank Gollan Ankori, Shaked Sukiennik, Einav Avraham, Noam Davidov, and Ellah Richter for their work on manually coding the Hebrew-specific predictors and help in data collection. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | SPRINGER NATURE | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/ERC/692502-L2STAT | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.subject | Visual word recognition | es_ES |
dc.subject | Mega studies | es_ES |
dc.subject | reading | es_ES |
dc.subject | Cross-linguistic differences | es_ES |
dc.title | HeLP: The Hebrew Lexicon project | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | Open Access This article is licensed under a Creative Commons Attribution
4.0 International License, which permits use, sharing, adaptation,
distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
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need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. | es_ES |
dc.relation.publisherversion | https://link.springer.com/journal/13428 | es_ES |
dc.identifier.doi | 10.3758/s13428-024-02502-4 | |