Article published In:
Scientific Study of LiteratureVol. 4:1 (2014) ► pp.46–67
The relationship between reading literary novels and predictive inference generation
A corpus-based approach employing a corpus of Japanese novels
Keisuke Inohara | Graduate School of Informatics and Engineering, University of Electro-Communications, Japan
This study examined the relationship between reading literary novels and generating predictive inferences by analyzing a corpus of Japanese novels. Latent semantic analysis (LSA) was used to capture the statistical structure of the corpus. Then, the authors asked 74 Japanese college students to generate predictive inferences (e.g., “The newspaper burned”) in response to Japanese event sentences (e.g., “A newspaper fell into a bonfire”) and obtained more than 5,000 predicted events. The analysis showed a significant relationship between LSA similarity between the event sentences and the predicted events and frequency of the predicted events. This result suggests that exposure to literary works may help develop readers’ inference generation skills. In addition, two vector operation methods for sentence vector constructions from word vectors were compared: the “Average” method and the “Predication Algorithm” method (Kintsch, 2001). The results support the superiority of the Predication Algorithm method over the Average method.
References (55)
Altmann, G.T.M., & Kamide, Y. (1999). Incremental interpretation at verbs: restricting the domain of subsequent reference. Cognition, 73(3), 247–264. 
Biber, D. (2011). Corpus linguistics and the study of literature: Back to the future? Scientific Study of Literature, 1(1), 15–23.
Cain, K., Oakhill, J.V., & Elbro, C. (2003). The ability to learn new word meanings from context by school-age children with and without language comprehension difficulties. Journal of Child Language, 30(3), 681–694.
Chwilla, D.J., & Kolk, H.H.J. (2002). Three-step priming in lexical decision. Memory and Cognition, 30(2), 217–225.
Denhiere, G., Lemaire, B., Bellissens, C., & Jhean-Larose, S. (2007). A semantic space for modeling children’s semantic memory. In T.K. Landauer, D.S. McNamara, S. Dennis & W. Kintsch (Eds.), Handbook of latent semantic analysis (pp. 143–166). Mahwah, NJ: Lawrence Erlbaum Associates.
Dixon, P., & Bortolussi, M. (2011). The scientific study of literature: What can, has, and should be done. Scientific Study of Literature, 1(1), 59–71.
Dunst, C.J., Simkus, A., & Hamby, D.W. (2012). Effects of reading to infants and toddlers on their early language development. Center for Early Literacy Learning, 5(4), 1–7.
Elman, J.L. (1991). Distributed representations, simple recurrent networks, and grammatical structure. Mach. Learn., 7(2-3), 195–225.
Fincher-Kiefer, R. (1995). Relative inhibition following the encoding of bridging and predictive inferences. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21(4), 981–995.
. (1996). Encoding differences between bridging and predictive inferences. Discourse Processes, 22(3), 225–246.
Foltz, P.W., Kintsch, W., & Landauer, T.K. (1998). The measurement of textual coherence with latent semantic analysis. Discourse Processes, 25(2-3), 285–307.
Graesser, A.C., & McNamara, D.S. (2011). Computational analyses of multilevel discourse comprehension. Topics in Cognitive Science, 3(2), 371–398.
Graesser, A.C., Singer, M., & Trabasso, T. (1994). Constructing inferences during narrative text comprehension. Psychological Review, 101(3), 371–395.
Griffiths, T.L., Steyvers, M., & Tenenbaum, J.B. (2007). Topics in semantic representation. Psychological Review, 114(2), 211–244.
Hare, M., Jones, M., Thomson, C., Kelly, S., & McRae, K. (2009). Activating event knowledge. Cognition, 111(2), 151–167.
Hutchison, K.A., Balota, D.A., Cortese, M.J., & Watson, J.M. (2008). Predicting semantic priming at the item level. Quarterly Journal of Experimental Psychology, 61(7), 1036–1066.
Inohara, K., & Kusumi, T. (2012). Effect of reading habits on vocabulary: examination by latent semantic analysis. Cognitive studies : bulletin of the Japanese Cognitive Science Society, 191, 100–121.
Iseki, R. (2006). Which regulates on-line inference generation in text comprehension, coherence or accessibility? Cognitive studies : bulletin of the Japanese Cognitive Science Society, 131, 205–224.
Jones, M.N., Kintsch, W., & Mewhort, D.J.K. (2006). High-dimensional semantic space accounts of priming. Journal of Memory and Language, 55(4), 534–552.
Jones, M.N., & Mewhort, D.J.K. (2007). Representing word meaning and order information in a composite holographic lexicon. Psychological Review, 114(1), 1–37.
Kamide, Y., Altmann, G.T.M., & Haywood, S.L. (2003). The time-course of prediction in incremental sentence processing: Evidence from anticipatory eye movements. Journal of Memory and Language, 49(1), 133–156.
Keefe, D.E., & McDaniel, M.A. (1993). The timecourse and durability of predictive inferences. Journal of Memory and Language, 32(4), 446–463.
Kidd, D.C., & Castano, E. (2013). Reading literary fiction improves theory of mind. Science, 342(6156), 377–380.
Kintsch, W. (1998). Comprehension: a paradigm for cognition: Cambridge university press.
. (2000). Metaphor comprehension: a computational theory. Psychonomic Bulletin & Review, 7(2), 257–266.
. (2001). Predication. Cognitive Science, 25(2), 173–202.
Kintsch, W., & Bowles, A.R. (2002). Metaphor comprehension: what makes a metaphor difficult to understand? Metaphor and Symbol, 17(4), 249–262.
Kudo, T. (2005). MeCab: yet another part-of-speech and morphological analyzer. Retrieved from [URL]
Landauer, T.K., & Dumais, S.T. (1997). A solution to Plato’s problem: the latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review, 104(2), 211–240.
Landauer, T.K., Foltz, P.W., & Laham, D. (1998). An introduction to latent semantic analysis. Discourse Processes, 25(2-3), 259–284.
Lund, K., & Burgess, C. (1996). Producing high-dimensional semantic spaces from lexical co-occurrence. Behavior Research Methods Instruments & Computers, 28(2), 203–208.
Magliano, J.P., Baggett, W.B., Johnson, B.K., & Graesser, A.C. (1993). The time course of generating causal antecedent and causal consequence inferences. Discourse Processes, 16(1-2), 35–53.
McKoon, G., & Ratcliff, R. (1986). Inferences about predictable events. Journal of Experimental Psychology-Learning Memory and Cognition, 12(1), 82–91.
Miall, D.S. (2011). Science in the perspective of literariness. Scientific Study of Literature, 1(1), 7–14.
Mol, S.E., & Bus, A.G. (2011). To read or not to read: a meta-analysis of print exposure from infancy to early adulthood. Psychological Bulletin, 137(2), 267–296.
National Institute for Japanese Language and Linguistics. (2009). Modern Japanese balanced written language corpus 2009 monitor edition. Retrieved from: [URL]
Pacton, S., Fayol, M., & Perruchet, P. (2005). Children’s implicit learning of graphotactic and morphological regularities. Child Development, 76(2), 324–339.
Pacton, S., Perruchet, P., Fayol, M., & Cleeremans, A. (2001). Implicit learning out of the lab: the case of orthographic regularities. Journal of Experimental Psychology: General, 130(3), 401–426.
Potts, G.R., Keenan, J.M., & Golding, J.M. (1988). Assessing the occurrence of elaborative inferences: lexical decision versus naming. Journal of Memory and Language, 27(4), 399–415.
Quesada, J. (2007). Creating your own LSA space. In T.K. Landauer, D.S. McNamara, S. Dennis & W. Kintsch (Eds.), Handbook of latent semantic analysis (pp. 71–85). Mahwah, NJ: Lawrence Erlbaum Associates.
Schmalhofer, F., McDaniel, M.A., & Keefe, D. (2002). A unified model for predictive and bridging inferences. Discourse Processes, 33(2), 105–132.
Senechal, M. (2006). Testing the home literacy model: parent involvement in kindergarten is differentially related to grade 4 reading comprehension, fluency, spelling, and reading for pleasure. Scientific Studies of Reading, 10(1), 59–87.
Stanovich, K.E. (1986). Matthew effects in reading: some consequences of individual differences in the acquisition of literacy. Reading Research Quarterly, 360–407.
Stanovich, K.E., Cunningham, A.E., & West, R.F. (1998). Literacy experiences and the shaping of cognition. Global prospects for education: Development, culture, and schooling, 253–288.
Stanovich, K.E., & West, R.F. (1989). Exposure to print and orthographic processing. Reading Research Quarterly, 24(4), 402–433.
Swanborn, M.S.L., & de Glopper, K. (1999). Incidental word learning while reading: a meta-analysis. Review of Educational Research, 69(3), 261–285.
Swanborn, M.S.L., & De Glopper, K. (2002). Impact of reading purpose on incidental word learning from context. Language Learning, 52(1), 95–117.
Utsumi, A. (2011). Computational exploration of metaphor comprehension processes using a semantic space model. Cognitive Science, 35(2), 251–296.
van Peer, W. (2011). Introduction. Scientific Study of Literature 1(1), 1–5.
Wolfe, M.B.W. (2005). Memory for narrative and expository text: independent influences of semantic associations and text organization. Journal of Experimental Psychology-Learning Memory and Cognition, 31(2), 359–364.
Wolfe, M.B.W., Magliano, J.P., & Larsen, B. (2005). Causal and semantic relatedness in discourse understanding and representation. Discourse Processes,39(2-3), 165–187.
Zacks, J.M., Speer, N.K., & Reynolds, J.R. (2009). Segmentation in reading and film comprehension. Journal of Experimental Psychology: General, 138(2), 307–327.
Zacks, J.M., & Swallow, K.M. (2007). Event segmentation. Current Directions in Psychological Science, 16(2), 80–84.
Zwaan, R.A. (1994). Effect of genre expectations on text comprehension. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20(4), 920–933.
Zwaan, R.A., & Radvansky, G.A. (1998). Situation models in language comprehension and memory. Psychological Bulletin, 123(2), 162–185.