UJEDNAČENOST VEROVATNOĆA ZNAČENJA I OBRADA HOMONIMIJE U SRPSKOM JEZIKU

  • Dušica Filipović Đurđević
Ključne reči: broj značenja, entropija, homonimija, redundansa, zadatak vizuelne leksičke odluke

Apstrakt

U ovom istraživanju grupa homonimnih imenica srpskog jezika (imenica sa višestrukim nepovezanim značenjima) izlagana je u normativnoj studiji i u eksperimentu sa zadatkom vizuelne leksičke odluke. Govornici, kojima je srpski jezik maternji, navodili su značenja homonima i procenjivali reči na skali familijarnosti i konkretnosti. Na osnovu njih, formirana je prva baza homonima srpskog jezika, koja sadrži značenja homonimnih imenica srpskog jezika koja su poznata ispitanicima, kao i procenjene verovatnoće svakog značenja, broj značenja, redundansu i entorpiju distribucije verovatnoće značenja, poznatost reči i konkretnost. U zadatku vizuelne leksičke odluke ponovljen je nalaz o sporijoj obradi homonima u odnosu na jednoznačne reči. Dodatno, obrada homonimnih imenica dovedena je u vezi sa redundansom – informaciono-teorijskom merom koja opisuje ujednačenost verovatnoća značenja. Rezultati su pokazali da su homonimi sa većom redundansom distribucije verovatnoća značenja (tj. neujednačenim verovatnoćama značenja) imali kraće vreme prepoznavanja. Ovaj nalaz je u skladu sa predikcijom izvedenom iz pristupa obradi višeznačnih reči koji se zasniva na dinamici razrešavanja značenja, po kojoj kompeticija između nepovezanih značenja dovodi do sporije obrade homonima. Međutim, u slučaju broja značenja i entropije, obrazac rezultata je donekle odstupao, zbog čega je potrebno nastaviti sa itraživanjem obrade višeznačnih reči.

Biografija autora

Dušica Filipović Đurđević

Odeljenje za psihologiju, Filozofski fakultet, Univerzitet u Beogradu
Laboratorija za eksperimentalnu psihologiju, Filozofski fakultet, Univerzitet u Beogradu
Laboratorija za eksperimentalnu psihologiju, Filozofski fakultet, Univerzitet u Novom Sadu

Reference

Armstrong, B. C. (2012). The Temporal dynamics of word comprehension and response selection: Computational and behavioral studies. (Unpublished doctoral dissertation) of Philosophy). Psychology Department, Carnegie Mellon University, Pennsylvania.

Armstrong, B. C., & Plaut, D. C. (2016). Disparate semantic ambiguity effects from semantic processing dynamics rather than qualitative task differences. Language, Cognition, and Neuroscience, 1(7), 1–27. doi:10.1080/23273798.201 6.1171366

Armstrong, B. C., Tokowicz, N., & Plaut, D. C. (2012). eDom: Norming software and relative meaning frequencies for 544 English homonyms. Behavior Research Methods, 44, 1015–1027. doi:10.3758/s13428-012-0199-8

Azuma, T. (1996). Familiarity and relatedness of word meanings: Ratings for 110 homographs. Behavior Research Methods, Instruments, and Computers, 28(1), 109–124. doi:10.3758/BF03203645

Azuma, T., & Van Orden, G. C. (1997). Why SAFE Is Better Than FAST: The Relatedness of a Word’s Meanings Affects Lexical Decision Times. Journal of Memory and Language, 36(4), 484–504. doi:10.1006/jmla.1997.2502

Baayen, R. H., & Milin, P. (2010). Analyzing reaction times. International Journal of Psychological Research, 32, 12–28. doi:10.21500/20112084.807

Balota, D. A., Pilotti, M., & Cortese, M. J. (2001). Subjective frequency estimates for 2,938 monosyllabic words. Memory and Cognition, 29, 639–647. doi:10.3758/ BF03200465

Borowsky, R., & Masson, M. E. J. (1996). Semantic ambiguity effects in word identification. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22(1), 63–85. doi:10.1037//0278-7393.22.1.63

Clark, H. H. (1973). The Language-as-Fixed-Effect-Fallacy: A Critique of Language Statistics in Psychological Research. Journal of Verbal Learning and Verbal Behavior, 12, 335–359. doi:10.1016/S0022-5371(73)80014-3

Coltheart, M., Davelaar, E., Jonasson, J. T., & Besner, D. (1977). Access to the internal lexicon. In S. Dornic (Ed.), Attention and performance VI (pp. 535–555). NJ: Erlbaum.

Cover, T. M., & Thomas, J. A. (1991). Elements of information theory. New York: John Wiley & Sons. doi:10.1002/0471200611

Eddington, C. M., & Tokowicz, N. (2015). How meaning similarity influences ambiguous word processing: the current state of the literature. Psychonomic Bulletin & Review, 22(1), 13–37. doi:10.3758/s13423-014-0665-7

Ferraro, F. R., & Kellas, G. (1990). Normative data for number of word meanings. Behavior Research Methods, Instruments, and Computers, 22(6), 491–498. doi:10.3758/BF03204432

Filipović Đurđević, D. (2007). Polysemy effect in processing of Serbian nouns (Unpublished doctoral dissertation). University of Belgrade, Serbia.

Filipović Đurđević, D. (2018). Naïve discrimination learning approach to polysemy. Proceedings of the XXIV Scientific Conference Empirical Studies in Psychology. March 23-25, 2018, Faculty of Philosophy, University of Belgrade, Institute of Psychology, Laboratory for Experimental Psychology, Faculty of Philosophy, University of Belgrade, 63–64.

Filipović Ðurđević, D., Ðurđević, Đ., & Kostić, A. (2009). Vector based semantic analysis reveals absence of competition among related senses. Psihologija, 42, 95–106. doi:10.2298/PSI0901095F

Filipović Đurđević, D., & Kostić, A. (2008). The effect of polysemy on processing of Serbian nouns. Psihologija, 41(1), 69–86. doi:10.2298/PSI0801059F

Filipović Đurđević, D., & Kostić, A. (2017). Number, Relative Frequency, Entropy, Redundancy, Familiarity, and Concreteness of Word Senses: Ratings for 150 Serbian Polysemous Nouns. In S. Halupka-Rešetar & S. Martínez-Ferreiro (Eds.) Studies in Language and Mind 2 (pp. 13–77). Novi Sad: Filozofski fakultet.

Filipović Đurđević, D., & Kostić, A. We probably sense sense probabilities. Under review.

Gawlick-Grendell, L. A., & Woltz, D. J. (1994). Meaning dominance norms for 120 homographs. Behavior Research Methods, Instruments, and Computers, 26(1), 5–25. doi:10.3758/BF03204557

Gelman, A., & Hill, J. (2007). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge: Cambridge University Press. doi:10.1017/ CBO9780511790942

Gernsbacher, M. A. (1984). Resolving 20 years of inconsistent interactions between lexical familiarity and orthography, concreteness, and polysemy. Journal of Experimental Psychology: General, 113, 256–281. doi:10.1037/0096-3445.113.2.256

Gilhooly, K. J., & Logie, R. H. (1980). Age-of-acquisition, imagery, concreteness, familiarity, and ambiguity measures for 1,944 words. Behavior Research Methods & Instrumentation, 12(4), 395–427. doi:10.3758/BF03201693

Hino, Y., & Lupker, S. J. (1996). Effects of polysemy in lexical decision and naming: An alternative to lexical access accounts. Journal of Experimental Psychology: Human Perception and Performance, 22(6), 1331–1356. doi:10.1037//0096-1523.22.6.1331

Jastrzembski, J. E. (1981). Multiple meanings, number of related meanings, frequency of occurrence, and the lexicon. Cognitive Psychology, 13(2), 278–305. doi:10.1016/0010-0285(81)90011-6

Kellas, G., Ferraro, R. R., & Simpson, G. B. (1988). Lexical Ambiguity and the Timecourse of Attentional Allocation In Word Recognition. Journal of Experimental Psychology: Human Perception and Performance, 14(4), 601–609. doi:10.1037//0096-1523.14.4.601

Kostić, Đ. (1999). Frekvencijski rečnik savremenog srpskog jezika [Frequency Dictionary of Contemporary Serbian Language]. Beograd: Institut za eksperimentalnu fonetiku i patologiju govora i Laboratorija za eksperimentalnu psihologiju.

Mathôt, S., Schreij, D., & Theeuwes, J. (2012). OpenSesame: An open-source, graphical experiment builder for the social sciences. Behavior Research Methods, 44(2), 314–324. doi:10.3758/s13428-011-0168-7

Medeiros, J., & Armstrong, B. C. (2017). Semantic Ambiguity Effects: A Matter of Time? In Proceedings of the 39th Annual Conference of the Cognitive Science Society, pp. 2693–2698. Mahwah, N: Lawrence Erlbaum Associates.

Millis, M. L., & Bution, S. B. (1989). The effect of polysemy on lexical decision time: Now you see it, now you don’t. Memory & Cognition, 17(2), 141–147. doi:10.3758/BF03197064

Paivio, A., Yuille, J. C., & Madigan, S. A. (1968). Concreteness, imagery, and meaningfulness values for 925 nouns. Journal of Experimental Psychology, 76(1p2), 1–25. doi:10.1037/h0025327

R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: https://www.R-project.org/

Rice, C., Beekhuizen, B., Dubrovsky, V., Stevenson, S., & Armstrong, B. C. (2018). A comparison of homonym meaning frequency estimates derived from movie and television subtitles, free association, and explicit ratings. Behavior Research Methods, 50, 1399–1425. doi:10.3758/s13428-018-1107-7

RMS – Rečnik Matice Srpske. (1967 – 1976). Rečnik srpskohrvatskoga književnog jezika, t. I-VI [Dictionary of Serbo-Croatian literary language]. Novi Sad: Matica Srpska.

Rodd, J. M., Gaskell, M. G., & Marslen-Wilson, W. D. (2002). Making sense of semantic ambiguity: Semantic competition in lexical access. Journal of Memory and Language, 46, 245–266. doi:10.1006/jmla.2001.2810

Rodd, J. M., Gaskell, M. G., & Marslen-Wilson, W. D. (2004). Modelling the effects of semantic ambiguity in word recognition. Cognitive Science, 28, 89–104. doi:10.1207/s15516709cog2801_4

Rubenstein, H., Garfield, L., & Millikan, J. A. (1970). Homographic entries in the internal lexicon. Journal of Verbal Learning and Verbal Behavior, 9(5), 487–494. doi:10.1016/S0022-5371(70)80091-3

Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379–423. doi:10.1002/j.1538-7305.1948.tb01338.x

Twilley, L. C., Dixon, P., Taylor, D., & Clark, K. (1994). University of Alberta norms of relative meaning frequency for 566 homographs. Memory and Cognition, 22(1), 111–126. doi:10.3758/BF03202766

Van Rij, J., Wieling, M., Baayen, R., & van Rijn, H. (2017). “itsadug: Interpreting Time Series and Autocorrelated Data Using GAMMs”. R package version 2.3.

Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. New York: Springer-Verlag. doi:10.1007/978-3-319-24277-4_9

Wood, S. N. (2006). Generalized Additive Models: An Introduction with R. Chapman and Hall/CRC. MY, Florida: Boca Raton. doi:10.1201/9781420010404

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, 731, 3–36. doi:10.1111/j.1467-9868.2010.00749.x
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