From eye movements to scanpath networks: A method for studying individual differences in expository text reading

Xiaochuan Ma, Yikang Liu, Roy Clariana, Chanyuan Gu, Ping Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review


Eye movements have been examined as an index of attention and comprehension during reading in the literature for over 30 years. Although eye-movement measurements are acknowledged as reliable indicators of readers’ comprehension skill, few studies have analyzed eye-movement patterns using network science. In this study, we offer a new approach to analyze eye-movement data. Specifically, we recorded visual scanpaths when participants were reading expository science text, and used these to construct scanpath networks that reflect readers’ processing of the text. Results showed that low ability and high ability readers’ scanpath networks exhibited distinctive properties, which are reflected in different network metrics including density, centrality, small-worldness, transitivity, and global efficiency. Such patterns provide a new way to show how skilled readers, as compared with less skilled readers, process information more efficiently. Implications of our analyses are discussed in light of current theories of reading comprehension.
Original languageEnglish
JournalBehavior Research Methods
Publication statusPublished - 20 Apr 2022


  • Eye tracking
  • Knowledge representation
  • Network metrics
  • Reading comprehension
  • Scanpath

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Psychology (miscellaneous)
  • Psychology(all)

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