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 reflects 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.
M. Fuyama—Please note that the LNCS Editorial assumes that all authors have used the western naming convention, with given names preceding surnames. This determines the structure of the names in the running heads and the author index.
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Acknowledgements
The authors are grateful to Dr. Neeraj Kashyap for his proofreading of this manuscript. The first author was supported by the Keio University Doctorate Student Grant-in-Aid Program and Mori Grants. The second author was supported by the Grant-in-Aid for Scientific Research B KAKENHI No. 23300099.
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Fuyama, M., Hidaka, S. (2017). Identifying Context-Dependent Modes of Reading. In: Otake, M., Kurahashi, S., Ota, Y., Satoh, K., Bekki, D. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2015. Lecture Notes in Computer Science(), vol 10091. Springer, Cham. https://doi.org/10.1007/978-3-319-50953-2_38
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DOI: https://doi.org/10.1007/978-3-319-50953-2_38
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