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Related Experiment Video

Updated: May 28, 2026

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

Measuring local context as context-word probabilities.

Lance W Hahn1

  • 1Department of Psychology, Western Kentucky University, 1906 College Heights Blvd. #21030, Bowling Green, KY 42101, USA. Lance.Hahn@WKU.edu

Behavior Research Methods
|October 1, 2011
PubMed
Summary
This summary is machine-generated.

Researchers developed a new method to measure how well a word fits a sentence context using language usage statistics. This new measure correlates well with traditional cloze probability, improving reading research.

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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
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Related Experiment Videos

Last Updated: May 28, 2026

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Area of Science:

  • Cognitive Psychology
  • Psycholinguistics
  • Computational Linguistics

Background:

  • Sentence context influences word recognition, with related words recognized faster and unrelated words slower.
  • Cloze probability, the likelihood of a word completing a sentence, has been used to estimate context-word relatedness.
  • Existing methods for estimating context-word relatedness may not cover all sentence contexts.

Purpose of the Study:

  • To develop and validate a new measure of local context-word relatedness based on common language usage.
  • To demonstrate the effectiveness of this new measure in reflecting variations in context relevant to reading.

Main Methods:

  • Calculating conditional probabilities of word sequences from large text corpora.
  • Correlating these conditional probabilities with established cloze probabilities from existing studies.
  • Developing a composite measure incorporating conditional probabilities from one- to four-word contexts and sentence-ending punctuation.

Main Results:

  • Conditional probabilities derived from four-word contexts significantly correlated with cloze probabilities.
  • A composite context measure, including one- to four-word contexts and sentence-ending punctuation, showed significant correlations (.25, .52, .53) with cloze probabilities.
  • The proposed measure demonstrated variations consistent with the N400 effect, suggesting its relevance to reading processes.

Conclusions:

  • A novel, composite measure effectively estimates local context-word relatedness using language usage statistics.
  • This measure provides a robust alternative for analyzing context effects in reading research.
  • The findings support the role of local context in cognitive processes during reading.