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<p>The collection of large-scale lexical decision data has introduced a methodological shift in the psycholinguistic field, enabling researchers to perform virtual experiments on many lexical items without the inherent restrictions imposed by standard factorial design. However, Modern Standard Arabic (MSA) lacks such a resource. Therefore, the current study developed, validated, and illustrated the advantage of a lexical decision database for MSA in three (virtual) experiments. In the Main Experiment, we used a visual lexical decision task to collect reaction time and accuracy data on 10,000 MSA words and 10,000 nonwords from 604 first-language (L1) speakers, and on a subset of these stimuli (<i>N</i> words = 1,000; <i>N</i> nonwords = 1,000) from 43 s-language (L2) MSA speakers. The collected data showed good reliability. In Virtual Experiment 1, we showed that our database largely replicates well-documented effects in visual word recognition (lexicality, word length, word frequency, word neighborhood size), establishing its validity. In Virtual Experiment 2, we revealed the significant role of three less-explored MSA-specific predictors (perceptual complexity, clitics, diglossic distance) on L1 and L2 MSA visual word recognition, demonstrating one potential application of the database. We make our database freely available to support research on MSA visual word recognition.</p>

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The Arabic Lexicon Project: Lexical decision data for 10,000 Modern Standard Arabic words

  • 期刊论文

  • 发表日期：

    2026年7月16日

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  • Alaa Alzahrani,
  • Hassan Alshumrani,
  • Wafa Aljuaythin,
  • Iman Mahfouz,
  • Laila Alsuwaiyan,
  • Noura Aljadaan,
  • Sharif Alghazo,
  • Imane Tiaiba,
  • Zaha Alanzi

摘要

The collection of large-scale lexical decision data has introduced a methodological shift in the psycholinguistic field, enabling researchers to perform virtual experiments on many lexical items without the inherent restrictions imposed by standard factorial design. However, Modern Standard Arabic (MSA) lacks such a resource. Therefore, the current study developed, validated, and illustrated the advantage of a lexical decision database for MSA in three (virtual) experiments. In the Main Experiment, we used a visual lexical decision task to collect reaction time and accuracy data on 10,000 MSA words and 10,000 nonwords from 604 first-language (L1) speakers, and on a subset of these stimuli (N words = 1,000; N nonwords = 1,000) from 43 s-language (L2) MSA speakers. The collected data showed good reliability. In Virtual Experiment 1, we showed that our database largely replicates well-documented effects in visual word recognition (lexicality, word length, word frequency, word neighborhood size), establishing its validity. In Virtual Experiment 2, we revealed the significant role of three less-explored MSA-specific predictors (perceptual complexity, clitics, diglossic distance) on L1 and L2 MSA visual word recognition, demonstrating one potential application of the database. We make our database freely available to support research on MSA visual word recognition.