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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/15261

Title: Identifying Context-dependent Modes of Reading
Authors: Fuyama, Miho
Hidaka, Shohei
Keywords: Literary
Reading-time analysis
Issue Date: 2017-04-12
Publisher: Springer
Magazine name: Lecture Notes in Artificial Intelligence
Volume: 10091
Start page: 514
End page: 527
DOI: 10.1007/978-3-319-50953-2_38
Abstract: Past literature has suggested that reading text as a whole cannot be reduced to merely an aggregation of sentence processing, but instead there are expected to be some context-dependent stylistic differences in the reading process. It has been, however, difficult to capture such context-dependent reading styles or modes. In this study, under the hypothesis that the statistics of reading time reffects such reading modes, we introduce a new statistical approach to capture them. Our analysis of the distributions of reading times identified two distinct modes of reading. In further analysis, we found that the temporal profiles of the two reading modes were correlated to the reader’s degree of engagement. We discuss how the context dependency of the reading modes is related to dynamic construction of the reader’s knowledge of narratives.
Rights: This is the author-created version of Springer, Miho Fuyama, Shohei Hidaka, Lecture Notes in Artificial Intelligence, 10091, 2017, 514-527. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/978-3-319-50953-2_38
URI: http://hdl.handle.net/10119/15261
Material Type: author
Appears in Collections:a10-1. 雑誌掲載論文 (Journal Articles)

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