Expanding horizons of cross-linguistic research on reading: The Multilingual Eye-movement Corpus (MECO)

Noam Siegelman*, Sascha Schroeder, Cengiz Acartürk, Hee Don Ahn, Svetlana Alexeeva, Simona Amenta, Raymond Bertram, Rolando Bonandrini, Marc Brysbaert, Daria Chernova, Sara Maria Da Fonseca, Nicolas Dirix, Wouter Duyck, Argyro Fella, Ram Frost, Carolina A. Gattei, Areti Kalaitzi, Nayoung Kwon, Kaidi Lõo, Marco MarelliTimothy C. Papadopoulos, Athanassios Protopapas, Satu Savo, Diego E. Shalom, Natalia Slioussar, Roni Stein, Longjiao Sui, Analí Taboh, Veronica Tønnesen, Kerem Alp Usal, Victor Kuperman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


Scientific studies of language behavior need to grapple with a large diversity of languages in the world and, for reading, a further variability in writing systems. Yet, the ability to form meaningful theories of reading is contingent on the availability of cross-linguistic behavioral data. This paper offers new insights into aspects of reading behavior that are shared and those that vary systematically across languages through an investigation of eye-tracking data from 13 languages recorded during text reading. We begin with reporting a bibliometric analysis of eye-tracking studies showing that the current empirical base is insufficient for cross-linguistic comparisons. We respond to this empirical lacuna by presenting the Multilingual Eye-Movement Corpus (MECO), the product of an international multi-lab collaboration. We examine which behavioral indices differentiate between reading in written languages, and which measures are stable across languages. One of the findings is that readers of different languages vary considerably in their skipping rate (i.e., the likelihood of not fixating on a word even once) and that this variability is explained by cross-linguistic differences in word length distributions. In contrast, if readers do not skip a word, they tend to spend a similar average time viewing it. We outline the implications of these findings for theories of reading. We also describe prospective uses of the publicly available MECO data, and its further development plans.

Original languageAmerican English
Pages (from-to)2843-2863
Number of pages21
JournalBehavior Research Methods
Issue number6
StatePublished - Dec 2022
Externally publishedYes

Bibliographical note

Funding Information:
Research reported in this publication was supported by the following grants: The Social Sciences and Humanities Research Council of Canada Partnered Research Training Grant, 895-2016-1008 (PI: G. Libben); the Canada Research Chair (Tier 2; PI: V. Kuperman); the CFI Leaders Opportunity Fund (PI: V. Kuperman); Concerted research action BOF13/GOA/032 of Ghent University; FWO Project (PI: M. Brysbaert); Estonian Research Council Mobilitas Pluss postdoctoral researcher grant MOBJD408 (PI: K. Lõo); ERC Advanced grant, project 692502-L2STAT (PI: R. Frost); the Israel Science Foundation (ISF) grant 48/20 (PI: N. Siegelman); and Saint Petersburg State University grant ID 75288744, 121050600033-7 (PI: N. Slioussar). We wish to thank the following individuals: Mariam Bekhet, Paige Cater, John Connolly, Melda Coskun Karadag, Connie Imbault, Alyssa Janes, Shani Kahta, Minji Kang, Evgenia-Peristera Kouki, Elizaveta Kuzmina, Nadia Lana, Sean McCarron, Kelly Nisbet, Victoria Ong, Anat Prior, Eva Saks, Elisabet Service, Anna Swain, Heather Wild, Sophia Yang, and Laoura Ziaka. Thanks are due to Ralph Radach and two anonymous reviewers for valuable comments to earlier drafts.

Publisher Copyright:
© 2022, The Psychonomic Society, Inc.


  • Cross-linguistic research
  • Eye tracking
  • Language
  • Reading


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