Reading Shakespeare sonnets: Combining quantitative narrative analysis and predictive modeling - an eye tracking study

As a part of a larger interdisciplinary project on Shakespeare sonnets’ reception (Jacobs et al., 2017; Xue et al., 2017), the present study analyzed the eye movement behavior of participants reading three of the 154 sonnets as a function of seven lexical features extracted via Quantitative Narrativ...

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Main Authors: Shuwei Xue, Jana Lüdtke, Teresa Sylvester, Arthur M. Jacobs
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Journal of Eye Movement Research
Subjects:
Online Access:https://bop.unibe.ch/JEMR/article/view/4460
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author Shuwei Xue
Jana Lüdtke
Teresa Sylvester
Arthur M. Jacobs
author_facet Shuwei Xue
Jana Lüdtke
Teresa Sylvester
Arthur M. Jacobs
author_sort Shuwei Xue
collection DOAJ
description As a part of a larger interdisciplinary project on Shakespeare sonnets’ reception (Jacobs et al., 2017; Xue et al., 2017), the present study analyzed the eye movement behavior of participants reading three of the 154 sonnets as a function of seven lexical features extracted via Quantitative Narrative Analysis (QNA). Using a machine learning- based predictive modeling approach five ‘surface’ features (word length, orthographic neighborhood density, word frequency, orthographic dissimilarity and sonority score) were detected as important predictors of total reading time and fixation probability in poetry reading. The fact that one phonological feature, i.e., sonority score, also played a role is in line with current theorizing on poetry reading. Our approach opens new ways for future eye movement research on reading poetic texts and other complex literary materials (cf. Jacobs, 2015c).
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spelling doaj-art-1b2644d9eb474dc49cf2ab130b2f5fff2025-08-20T01:59:05ZengMDPI AGJournal of Eye Movement Research1995-86922019-03-0112510.16910/jemr.12.5.2Reading Shakespeare sonnets: Combining quantitative narrative analysis and predictive modeling - an eye tracking studyShuwei Xue0Jana Lüdtke1Teresa Sylvester2Arthur M. Jacobs3Department of Experimental and Neurocognitive Psychology, Freie Universität Berlin, GermanyDepartment of Experimental and Neurocognitive Psychology, Freie Universität Berlin, GermanyDepartment of Experimental and Neurocognitive Psychology, Freie Universität Berlin, GermanyDepartment of Experimental and Neurocognitive Psychology, Freie Universität Berlin, Germany; Dahlem Institute for Neuroimaging of Emotion (D.I.N.E.), Berlin, Germany; Center for Cognitive Neuroscience Berlin (CCNB), Berlin, GermanyAs a part of a larger interdisciplinary project on Shakespeare sonnets’ reception (Jacobs et al., 2017; Xue et al., 2017), the present study analyzed the eye movement behavior of participants reading three of the 154 sonnets as a function of seven lexical features extracted via Quantitative Narrative Analysis (QNA). Using a machine learning- based predictive modeling approach five ‘surface’ features (word length, orthographic neighborhood density, word frequency, orthographic dissimilarity and sonority score) were detected as important predictors of total reading time and fixation probability in poetry reading. The fact that one phonological feature, i.e., sonority score, also played a role is in line with current theorizing on poetry reading. Our approach opens new ways for future eye movement research on reading poetic texts and other complex literary materials (cf. Jacobs, 2015c).https://bop.unibe.ch/JEMR/article/view/4460Literary readingeye movementseye trackingQNApredictive modeling
spellingShingle Shuwei Xue
Jana Lüdtke
Teresa Sylvester
Arthur M. Jacobs
Reading Shakespeare sonnets: Combining quantitative narrative analysis and predictive modeling - an eye tracking study
Journal of Eye Movement Research
Literary reading
eye movements
eye tracking
QNA
predictive modeling
title Reading Shakespeare sonnets: Combining quantitative narrative analysis and predictive modeling - an eye tracking study
title_full Reading Shakespeare sonnets: Combining quantitative narrative analysis and predictive modeling - an eye tracking study
title_fullStr Reading Shakespeare sonnets: Combining quantitative narrative analysis and predictive modeling - an eye tracking study
title_full_unstemmed Reading Shakespeare sonnets: Combining quantitative narrative analysis and predictive modeling - an eye tracking study
title_short Reading Shakespeare sonnets: Combining quantitative narrative analysis and predictive modeling - an eye tracking study
title_sort reading shakespeare sonnets combining quantitative narrative analysis and predictive modeling an eye tracking study
topic Literary reading
eye movements
eye tracking
QNA
predictive modeling
url https://bop.unibe.ch/JEMR/article/view/4460
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AT teresasylvester readingshakespearesonnetscombiningquantitativenarrativeanalysisandpredictivemodelinganeyetrackingstudy
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