{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T07:52:05Z","timestamp":1781769125007,"version":"3.54.5"},"reference-count":40,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T00:00:00Z","timestamp":1762128000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Union\u2013Next-Generation, Mission 4 Component 1","award":["2022JJ3PA5"],"award-info":[{"award-number":["2022JJ3PA5"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>In data visualization, users\u2019 scanning patterns are as crucial as their reading patterns in text-based media. Yet, no systematic attempt exists to characterize this activity with basic features, such as reading speed and scanpaths, nor to relate them to data complexity and information disposition. To fill this gap, this paper proposes a model-based method to analyze and interpret those features from eye-tracking data.\u00a0To this end, the bias-noise model is applied to a data visualization eye-tracking dataset available online, and enriched with areas of interest labels. The positive results of this method are as follows: (i) the identification of users\u2019 reading styles like meticulous, systematic, and serendipitous; (ii) the characterization of information disposition as gathered or scattered, and of information complexity as more or less dense; (iii) the discovery of a behavioural pattern of efficiency, given that the more visualizations were read by a participant, the greater their reading speed, consistency, and predictability of reading; (iv) the identification of\u00a0encoding and title areas of interest as the primary loci of attention in visualizations, with a peculiar back-and-forth reading pattern; (v) the identification of the encoding area of interest as the fastest to read in less dense visualization types, such as bars, circles, and lines\u00a0charts. Future experiments involving participants from diverse cultural backgrounds could not only validate the observed behavioural patterns, but also enrich the experimental framework with additional perspectives.<\/jats:p>","DOI":"10.3390\/fi17110504","type":"journal-article","created":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T17:32:01Z","timestamp":1762191121000},"page":"504","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Modeling Interaction Patterns in Visualizations with Eye-Tracking: A Characterization of Reading and Information Styles"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6740-8620","authenticated-orcid":false,"given":"Angela","family":"Locoro","sequence":"first","affiliation":[{"name":"Dipartimento di Economia e Management, Universit\u00e0 degli Studi di Brescia, Contrada Santa Chiara, 50, 25122 Brescia, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5226-4337","authenticated-orcid":false,"given":"Luigi","family":"Lavazza","sequence":"additional","affiliation":[{"name":"Dipartimento di Scienze Teoriche e Applicate, Universit\u00e0 degli Studi dell\u2019Insubria, Via O. Rossi, 9, 21100 Varese, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Majaranta, P., and Bulling, A. (2014). Eye tracking and eye-based human\u2013computer interaction. Advances in Physiological Computing, Springer.","DOI":"10.1007\/978-1-4471-6392-3_3"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1109\/TPAMI.2009.30","article-title":"In the Eye of the Beholder: A Survey of Models for Eyes and Gaze","volume":"32","author":"Hansen","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"813","DOI":"10.1007\/s11251-012-9218-5","article-title":"Conveying clinical reasoning based on visual observation via eye-movement modelling examples","volume":"40","author":"Jarodzka","year":"2012","journal-title":"Instr. 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