Wave 2 of the Multilingual Eye-Movement Corpus (MECO): New text reading data across languages

  • Noam Siegelman*
  • , Sascha Schroeder
  • , Yaqian Borogjoon Bao
  • , Cengiz Acartürk
  • , Niket Agrawal
  • , Lena S. Bolliger
  • , Jan Brasser
  • , César Campos-Rojas
  • , Denis Drieghe
  • , Dušica Filipović Đurđević
  • , Sofya Goldina
  • , Romualdo Ibáñez Orellana
  • , Lena A. Jäger
  • , Ómar I. Jóhannesson
  • , Anurag Khare
  • , Nik Kharlamov
  • , Hanne B.S. Knudsen
  • , Árni Kristjánsson
  • , Charlotte E. Lee
  • , Jun Ren Lee
  • Marina P.T. Leite, Simona Mancini, Nataša Mihajlović, Ksenija Mišić, Miloslava Orekhova, Olga Parshina, Milica Popović Stijačić, Athanassios Protopapas, David R. Reich, Anurag Rimzhim, Rui Rothe-Neves, Thais M.M. Sá, Andrea Santana-Covarrubias, Irina Sekerina, Heida M. Sigurdardottir, Anna Smirnova, Priyanka Srivastava, Elisangela N. Teixeira, Ivana Ugrinic, Kerem Alp Usal, Karolina Vakulya, Ark Verma, João M.M. Vieira, Denise H. Wu, Jin Xue, Sunčica Zdravković, Junjing Zhuo, Laoura Ziaka, Victor Kuperman
*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

This paper reports the Wave 2 expansion of the Multilingual Eye-Movement Corpus (MECO), a collaborative multi-lab project collecting eye-tracking data on text reading in a variety of languages. The present expansion comes with new eye-tracking data of N = 654 from 13 languages, collected in 16 labs over 15 countries, including in several languages that have little to no representation in current eye-tracking studies on reading. MECO also contains demographic, language use, and other individual differences data. This paper makes available the first-language reading data of MECO Wave 2 and incorporates reliability estimates of all tests at the participant and item level, as well as other methods of data validation. It also reports the descriptive statistics on all languages, including comparisons with prior similar data, and outlines directions for potential reuse.

Original languageEnglish
Article number1183
JournalScientific data
Volume12
Issue number1
DOIs
Publication statusPublished - 2025 Dec

ASJC Scopus subject areas

  • Statistics and Probability
  • Information Systems
  • Education
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

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