References (73)
References
Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In B. N. Petrov & F. Caski (Eds.), Proceedings of the Second International Symposium on Information Theory (pp. 267–281). Budapest: Akademiai Kiado.Google Scholar
(1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19 1, 716–723. DOI logoGoogle Scholar
Andrews, S. (1989). Frequency and neighborhood effects on lexical access: Activation or search? Journal of Experimental Psychology: Learning, Memory, and Cognition, 151, 802–814.Google Scholar
(1992). Frequency and neighborhood effects on lexical access: Lexical similarity or orthographic redundancy? Journal of Experimental Psychology: Learning, Memory, and Cognition, 181, 234–254.Google Scholar
(1997). The effect of orthographic similarity on lexical retrieval: Resolving neighborhood conflicts. Psychonomic Bulletin & Review, 4 (4), 439–461. DOI logoGoogle Scholar
Assink, E. M., Kattenberg, G., & Wortmann, C. (1998). Exploring the boundaries of sublexical word identification units: The use of onsets and rimes and reading ability. Journal of psycholinguistic research, 27 1, 639–659. DOI logoGoogle Scholar
Balota, D. A., Yap, M. J., Hutchison, K. A., Cortese, M. J., Kessler, B., Loftis, B., Neely, J., Nelson, D. L., Simpson, G. B., & Treiman, R. (2007). The English lexicon project. Behavior Research Methods, 39 (3), 445–459. DOI logoGoogle Scholar
Bateson, G. (1979). Mind and Nature: A Necessary Unity E.P. Dutton: New York, NY.Google Scholar
Bentz, C., Alikaniotis, D., Cysouw, M., & Ferrer-i-Cancho, R. (2017). The entropy of words — Learnability and expressivity across more than 1000 languages. Entropy, 19 (6), 275. DOI logoGoogle Scholar
Berlyne, D. E. (1971). Aesthetics and Psychobiology. New York: Appleton-Century-Crofts.Google Scholar
Blais, C., Fiset, D., Arguin, M., Jolicoeur, P., Bub, D., & Gosselin, F. (2009). Reading between eye saccades. PLoS One, 4(7), e6448. DOI logoGoogle Scholar
Booth, J. R., & Perfetti, C. A. (2002). Onset and rime structure influences naming but not early word identification in children and adults. Scientific Studies of Reading, 6 (1), 1–23. DOI logoGoogle Scholar
Bowey, J. A. (1990). Orthographic onsets and rimes as functional units of reading. Memory & Cognition, 18 (4), 419–427. DOI logoGoogle Scholar
Carhart-Harris, R. L., Leech, R., Hellyer, P. J., Shanahan, M., Feilding, A., Tagliazucchi, E., Chialvo, D. R., & Nutt, D. (2014). The entropic brain: a theory of conscious states informed by neuroimaging research with psychedelic drugs. Frontiers in human neuroscience, 8 1, 20. DOI logoGoogle Scholar
Carreiras, M., Perea, M., & Grainger, J. (1997). Effects of the orthographic neighborhood in visual word recognition: Cross-task comparisons. Journal of experimental psychology: learning, memory, and cognition, 23 (4), 857.Google Scholar
Chaitin, G. J. (1975). A theory of program size formally identical to information theory. Journal of the ACM, 22 (3), 329–340. DOI logoGoogle Scholar
Chen, Q., & Mirman, D. (2012). Competition and cooperation among similar representations: toward a unified account of facilitative and inhibitory effects of lexical neighbors. Psychological review, 119 (2), 417. DOI logoGoogle Scholar
Coltheart, M., Davelaar, E., Jonasson, J., & Besner, D. (1977). Access to the internal lexicon. In S. Dornic (Ed.), Attention and performance VI: Proceedings of the Sixth International Symposium on Attention and Performance, Stockholm, Sweden, July 28-August 1, 1975. Hillsdale, N.J: Lawrence Erlbaum.Google Scholar
Coupé, C., Oh, Y. M., Dediu, D., & Pellegrino, F. (2019). Different languages, similar encoding efficiency: Comparable information rates across the human communicative niche. Science Advances, 5 (9), eaaw2594. DOI logoGoogle Scholar
Davis, C. J., Perea, M., & Acha, J. (2009). Re (de) fining the orthographic neighborhood: The role of addition and deletion neighbors in lexical decision and reading. Journal of Experimental Psychology: Human Perception and Performance, 35 (5), 1550.Google Scholar
Duñabeitia, J. A., & Vidal-Abarca, E. (2008). Children like dense neighborhoods: Orthographic neighborhood density effects in novel readers. Spanish Journal of Psychology, 11 (1), 26. DOI logoGoogle Scholar
Dye, M., Johns, B. T., Jones, M. N., & Ramscar, M. (2016). The structure of names in memory: Deviations from uniform entropy impair memory for linguistic sequences. In A. Papafragou, D. Grodner, D. Mirman, & J. C. Trueswell (Eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society (pp. 1763–1768). Austin, TX: Cognitive Science Society.
Dye, M., Milin, P., Futrell, R. & Ramscar, M. (2017). A functional theory of gender paradigms. In: Kiefer, F., Blevins, J. P. and Bartos, H., (eds.) Perspectives on Morphological Structure: Data and Analyses. Brill, Leiden, pp. 212–239. DOI logoGoogle Scholar
Grainger, J., & Jacobs, A. M. (1993). Masked partial-word priming in visual word recognition: Effects of positional letter frequency. Journal of Experimental Psychology-Human Perception and Performance, 19(5), 951–964. DOI logoGoogle Scholar
(1996). Orthographic processing in visual word recognition: a multiple read-out model. Psychological Review, 103 (3), 518. DOI logoGoogle Scholar
Harati, P., Westbury, C., & Kiaee, M. (2021). Evaluating the predication model of metaphor comprehension: Using word2vec to model best/worst quality judgments of 622 novel metaphors. Behavior Research Methods, 53 (5), 2214–2225. DOI logoGoogle Scholar
Hastie, T. J. & Tibshirani, R. J. (1990). Generalized Additive Models. Chapman & Hall/CRC.Google Scholar
Heilbron, M., Armeni, K., Schoffelen, J. M., Hagoort, P., & De Lange, F. P. (2022). A hierarchy of linguistic predictions during natural language comprehension. Proceedings of the National Academy of Sciences, 119 (32), e2201968119. DOI logoGoogle Scholar
Hollis, G. (2018). Scoring best-worst data in unbalanced many-item designs, with applications to crowdsourcing semantic judgments. Behavior Research Methods, 50 ( 2 ), 711–729. DOI logoGoogle Scholar
(2020). The role of number of items per trial in best–worst scaling experiments. Behavior Research Methods, 52 (2), 694–722. DOI logoGoogle Scholar
Hollis, G., & Westbury, C. (2006). NUANCE: Naturalistic University of Alberta nonlinear correlation explorer. Behavior Research Methods, 38 (1), 8–23. DOI logoGoogle Scholar
(2018). When is best-worst best? A comparison of best-worst scaling, numeric estimation, and rating scales for collection of semantic norms. Behavior Research Methods, 50 1, 115–133. DOI logoGoogle Scholar
Hollis, G., Westbury, C. F., & Peterson, J. B. (2006). NUANCE 3.0: Using genetic programming to model variable relationships. Behavior research methods, 38 (2), 218–228. DOI logoGoogle Scholar
Huntsman, L. A., & Lima, S. D. (1996). Orthographic neighborhood structure and lexical access. Journal of Psycholinguistic Research, 25 (3), 417–429. DOI logoGoogle Scholar
Keuleers, E. (2013). vwr r package (v. 3). Downloaded from: [URL]
Keuleers, E., Lacey, P., Rastle, K., & Brysbaert, M. (2012). The British Lexicon Project: lexical decision data for 28,730 monosyllabic and disyllabic English words. Behavior Research Methods, 44 (1), 287–304. DOI logoGoogle Scholar
Kiritchenko, S., & Mohammad, S. M. (2016). Capturing reliable fine-grained sentiment associations by crowdsourcing and best-worst scaling. San Diego: Paper presented at the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL) . DOI logo
Levenshtein, V. I. (1966). Binary codes capable of correcting deletions, insertions and reversals. Soviet Physics Doklady, 101, 707.Google Scholar
Louviere, J. J., Flynn, T. N., & Marley, A. A. J. (2015). Best-worst scaling: Theory, methods and applications. Cambridge: Cambridge University Press. DOI logoGoogle Scholar
Luce, R. D. (2003). Whatever happened to information theory in psychology?. Review of General Psychology, 7 (2), 183–188. DOI logoGoogle Scholar
Luthra, S., You, H., Rueckl, J. G., & Magnuson, J. S. (2020). Friends in Low-Entropy Places: Orthographic Neighbor Effects on Visual Word Identification Differ Across Letter Positions. Cognitive Science, 44(12), e12917. DOI logoGoogle Scholar
McClelland, J. L., & Rumelhart, D. E. (1981). An interactive activation model of context effects in letter perception: I. An account of basic findings. Psychological review, 88 (5), 375. DOI logoGoogle Scholar
Miller, R. R., Barnet, R. C., & Grahame, N. J. (1995). Assessment of the Rescorla-Wagner model. Psychological Bulletin, 117 (3), 363. DOI logoGoogle Scholar
O’Regan, J. K., Lévy-Schoen, A., Pynte, J., & Brugaillière, B. (1984). Convenient fixation location within isolated words of different length and structure. Journal of Experimental Psychology: Human Perception and Performance, 10(3), 393.Google Scholar
Peereman, R., & Content, A. (1997). Orthographic and phonological neighborhoods in naming: Not all neighbors are equally influential in orthographic space. Journal of Memory and language, 37 (3), 382–410. DOI logoGoogle Scholar
Perea, M., & Rosa, E. (2000). The effects of orthographic neighborhood in reading and laboratory word identification tasks: A review. Psicológica, 21 (2), 327–340.Google Scholar
Piantadosi, S. T., Tily, H., & Gibson, E. (2011). Word lengths are optimized for efficient communication. Proceedings of the National Academy of Sciences, 108(9), 3526–3529. DOI logoGoogle Scholar
Pothos, E. (2010). An entropy model for artificial grammar learning. Frontiers in psychology, 1 1, 16. DOI logoGoogle Scholar
Ramscar, M., Dye, M., & Klein, J. (2013). Children value informativity over logic in word learning. Psychological science, 24 (6), 1017–1023. DOI logoGoogle Scholar
Ramscar, M., & Port, R. F. (2016). How spoken languages work in the absence of an inventory of discrete units. Language Sciences, 53 1, 58–74. DOI logoGoogle Scholar
Rayner, K., & Kaiser, J. S. (1975). Reading mutilated text. Journal of Educational Psychology, 671, 301–306. DOI logoGoogle Scholar
Rayner, K., White, S. J., Johnson, R. L., & Liversedge, S. P. (2006). Raeding wrods with jubmled lettres: There is a cost. Psychological Science, 171, 192–193. DOI logoGoogle Scholar
Rescorla, R. (1988). Pavlovian conditioning: it’s not what you think it is. American Psychologist, 43 1, 151–160. DOI logoGoogle Scholar
Rumelhart, D. E., & McClelland, J. L. (1982). An interactive activation model of context effects in letter perception: II. The contextual enhancement effect and some tests and extensions of the model. Psychological review, 89 (1), 60. DOI logoGoogle Scholar
Shannon, C. E. (1948). A note on the concept of entropy. Bell System Technical Journal, 27 1, 379–423. DOI logoGoogle Scholar
Sears, C. R., Hino, Y., & Lupker, S. J. (1995). Neighborhood size and neighborhood frequency effects in word recognition. Journal of Experimental Psychology: Human Perception and Performance, 21 (4), 876.Google Scholar
Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 271, 379–423 & 623–656. DOI logoGoogle Scholar
(1956). The bandwagon. IRE Transactions on Information Theory, 2 (1), 3. DOI logoGoogle Scholar
Shaoul, C. & Westbury, C. (2006). USENET Orthographic Frequencies for 111,627 English Words. (2005–2006) Edmonton, AB: University of Alberta (downloaded from [URL])
Siakaluk, P. D., Sears, C. R., & Lupker, S. J. (2002). Orthographic neighborhood effects in lexical decision: The effects of nonword orthographic neighborhood size. Journal of Experimental Psychology: Human Perception and Performance, 28(3), 661.Google Scholar
Sutton, R., & Barto, A. (1998). Reinforcement learning. Cambridge, MA: MIT Press.Google Scholar
Takahashi, T. (2013). A psychophysical theory of Shannon entropy. Neuroendocrinology Letters, 34 (7), 615–617.Google Scholar
Treiman, R. (1985). Onsets and rimes as units of spoken syllables: Evidence from children. Journal of experimental child psychology, 39 (1), 161–181. DOI logoGoogle Scholar
(1986). The division between onsets and rimes in English syllables. Journal of Memory and Language, 25 (4), 476–491. DOI logoGoogle Scholar
Treiman, R., Fowler, C. A., Gross, J., Berch, D., & Weatherston, S. (1995). Syllable structure or word structure? Evidence for onset and rime units with disyllabic and trisyllabic stimuli. Journal of Memory and Language, 34 (1), 132–155. DOI logoGoogle Scholar
Westbury, C. F., & Hollis, G. (2007). Putting Humpty together again: Synthetic approaches to nonlinear variable effects underlying lexical access. In G. Jarema & G. Libben (Eds.), The Mental Lexicon: Core perspectives (pp. 7–30). Bingley: Emerald. DOI logoGoogle Scholar
Westbury, C., Shaoul, C., Moroschan, G., & Ramscar, M. (2016). Telling the world’s least funny jokes: On the quantification of humor as entropy. Journal of Memory and Language, 86 1, 141–156. DOI logoGoogle Scholar
Westbury, C., Yang, M., and Anderson, K. (2024). The Principal Components of Meaning, Revisited. [Accepted for publication in Psychonomic Bulletin & Review]Google Scholar
Wood, S. N. (2011). Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. Journal of the Royal Statistical Society (B), 73(1), 3–36. DOI logoGoogle Scholar
Yarkoni, T., Balota, D., & Yap, M. (2008). Moving beyond Coltheart’s N: A new measure of orthographic similarity. Psychonomic Bulletin & Review, 15 ( 5 ), 971–979. DOI logoGoogle Scholar
Zhang, J. W., & Wang, Q. H. (2010). The orthographic neighborhood effect in word recognition. Advances in Psychological Science, 18 (06), 892–899.Google Scholar
Ziegler, J. C., & Perry, C. (1998). No more problems in Coltheart’s neighborhood: Resolving neighborhood conflicts in the lexical decision task. Cognition, 68 (2), B53–B62. DOI logoGoogle Scholar
Zipf, G. K. (1936). The Psychobiology of Language. Houghton-Mifflin: New York, NY.Google Scholar