Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/105481
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Title: Investigating differences in gaze and typing behavior across writing genres
Authors: Wang, J 
Fu, EY 
Ngai, G 
Leong, HV 
Issue Date: 2022
Source: International journal of human-computer interaction, 2022, v. 38, no. 6, p. 541-561
Abstract: Writing is one of the most common activities undertaken on a computer, and the activity of writing has been widely studied. Given that writing is an intensively cognitive process, it makes sense that the type of writing that is being produced would have an effect on the writer’s gaze and typing behaviors. However, only a few studies have explored this relationship. In this paper, we study the gaze-typing behaviors, specifically, the coordination between eye gaze and typing dynamics, of writers who are producing original articles in different genres: reminiscent, logical and creative. Our study focuses on Chinese typing, particularly via the Pinyin input method, which generates text via a two step method, and requires additional cognitive processes compared to typing in phonographic languages such as English. Our study involves 46 native Chinese speakers of varying ages from children to elderly. Our method deploys statistics- and sequence-based features to infer the mental state of the author during the writing process. The statistics-based features focus on modeling the overall gaze-typing behaviors during the process and the sequence-based features focus on the transition of the gaze-typing behaviors as the piece of writing progresses. Using a linear support-vector machine, we achieve an overall accuracy over 88% for the article-genre detection by using a leave-one-subject-out cross-validation evaluation.
Publisher: Taylor & Francis Inc.
Journal: International journal of human-computer interaction 
ISSN: 1044-7318
EISSN: 1532-7590
DOI: 10.1080/10447318.2021.1952801
Rights: © 2021 Taylor & Francis Group, LLC
This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Human–Computer Interaction on 10 August 2021 (published online), available at: https://tandfonline.com/10.1080/10447318.2021.1952801.
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