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The HeCz corpus: A large, richly annotated reading corpus of newspaper headlines in Czech

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11210%2F25%3A10510280" target="_blank" >RIV/00216208:11210/25:10510280 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=r6g.UBSF2A" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=r6g.UBSF2A</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3758/s13428-025-02863-4" target="_blank" >10.3758/s13428-025-02863-4</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    The HeCz corpus: A large, richly annotated reading corpus of newspaper headlines in Czech

  • Original language description

    Large behavioral datasets that provide detailed data on reading processes are valuable resources for a range of researchers working in linguistics, psychology and cognitive science. This paper presents the HeCz corpus, which comprises self-paced reading data for 1919 newspaper headlines (23,634 words) in Czech, with each headline being accompanied by a yes-no comprehension question, resulting in a rich dataset of reading times for each individual word and comprehension accuracy. The corpus is novel in terms of the sheer scale of data collection, with 1872 native Czech speakers, each reading approximately 120 headlines, with 1162 of those participants also completing the experiment again in a re-testing session using the same stimuli approximately 1 month later. There is participant level meta-data also available relating to basic demographic information, reading habits and a profile of their mood state prior to completing the experiment. Beyond the behavioral and demographic data, we also include a range of linguistic annotations for several variables, e.g., frequency, surprisal, morphological tagging. To better understand how these variables might impact processing, we present exploratory analyses where we predicted the reading times for words, with the results indicating important roles for linguistic, demographic, and methodological variables. Given the range of multidisciplinary applications of the HeCz corpus, we hope that it will provide a valuable and unprecedented resource for a range of research applications related to reading processes.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    60203 - Linguistics

Result continuities

  • Project

    <a href="/en/project/GA23-06796S" target="_blank" >GA23-06796S: Cze-Lex: A large-scale quantification of the Czech lexicon</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Behavior Research Methods

  • ISSN

    1554-351X

  • e-ISSN

    1554-3528

  • Volume of the periodical

    57

  • Issue of the periodical within the volume

    12

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    18

  • Pages from-to

    345

  • UT code for WoS article

    001614447500002

  • EID of the result in the Scopus database

    2-s2.0-105021828480