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Concreteness/Abstractness Concept: State of the Art

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Advances in Cognitive Research, Artificial Intelligence and Neuroinformatics (Intercognsci 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1358))

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Abstract

In recent years, several scientific disciplines – linguistics, psychology, psycholinguistics, neurophysiology, medicine, philosophy, education – have paid considerable attention to studying the concreteness/abstractness concept. Existing reviews on this topic cover only one area of research. This article provides an interdisciplinary overview from a general cognitive perspective and gives a general integral idea of this area. It is brief by necessity, but covers the main results obtained. First of all, this is the so-called “concreteness effect”, which consists in faster and more efficient processing of concrete words in comparison with abstract ones. The main theories explaining the effect of concreteness – the dual-coding theory and the context-availability theory – are considered. The problem of representing abstract and concrete words is one of the central problems in cognitive studies of the organization of concepts in our mind. The results of the search for neurophysiological correlates of concreteness/abstractness are discussed. In linguistics, fundamentally new research ideas and results have emerged due to large text corpora and large lexical ontologies. For research in these areas, it is important to have dictionaries with concreteness/abstractness ratings. The article provides data on the most significant dictionaries with human ratings for different languages, and also discusses how to extrapolate human ratings using machine learning methods. These methods, including deep learning of neural networks, can help quickly generate large dictionaries of near human quality, which can facilitate research in the field and extend it to many languages.

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References

  1. Paivio, A.: Abstractness, imagery, and meaningfulness in paired-associate learning. J. Verbal Learn. Verbal Behav. 4, 32–38 (1965). https://doi.org/10.1016/s0022-5371(65)80064-0

    Article  Google Scholar 

  2. Orena, E.F., Caldiroli, D., Acerbi, F., Barazzetta, I., Papagno, C.: Investigating the functional neuroanatomy of concrete and abstract word processing through direct electric stimulation (DES) during awake surgery. Cogn. Neuropsychol. 36(3–4), 167–177 (2018). https://doi.org/10.1080/02643294.2018.1477748

    Article  Google Scholar 

  3. Borghi, A.M., Binkofski, F., Castelfranchi, C., Cimatti, F., Scorolli, C., Tummolini, L.: The challenge of abstract concepts. Psychol. Bull. 143, 263–292 (2017)

    Article  Google Scholar 

  4. Mkrtychian, N., Blagovechtchenski, E., Kurmakaeva, D., Gnedykh, D., Kostromina, S., Shtyrov, Y.: Concrete vs. abstract semantics: from mental representations to functional brain mapping. Front. Hum. Neurosci. 13, 267 (2019). https://doi.org/10.3389/fnhum.2019.00267

    Article  Google Scholar 

  5. Vigliocco, G., Ponari, M., Norbury, C.: Learning and processing abstract words and concepts: insights from typical and atypical development. Top. Cogn. Sci. 10, 533–549 (2018). https://doi.org/10.1111/tops.12347

    Article  Google Scholar 

  6. Montefinese, M.: Semantic representation of abstract and concrete words: a minireview of neural evidence. J. Neurophysiol. 121, 1585–1587 (2019). https://doi.org/10.1152/jn.00065.2019

    Article  Google Scholar 

  7. Spreen, O., Schulz, R.W.: Parameters of abstraction, meaningfulness, and pronunciability for 329 nouns. J. Verbal Learn. Verbal Behav. 5, 459–468 (1966)

    Article  Google Scholar 

  8. Schmid, H.-J.: English Abstract Nouns as Conceptual Shells: From Corpus to Cognition. Topics in English Linguistics. De Gruyter Mouton (2000)

    Google Scholar 

  9. Schwanenflugel, P.J., Akin, C., Luh, W.-M.: Context availability and the recall of abstract and concrete words. Mem. Cogn. 20, 96–104 (1992). https://doi.org/10.3758/bf03208259

    Article  Google Scholar 

  10. Fliessbach, K., Weis, S., Klaver, P., Elger, C.E., Weber, B.: The effect of word concreteness on recognition memory. Neuroimage 32, 1413–1421 (2006). https://doi.org/10.1016/j.neuroimage.2006.06.007

    Article  Google Scholar 

  11. Schwanenflugel, P.J., Shoben, E.J.: Differential context effects in the comprehension of abstract and concrete verbal materials. J. Exp. Psychol. Learn. Mem. Cogn. 9, 82–102 (1983). https://doi.org/10.1037/0278-7393.9.1.82

    Article  Google Scholar 

  12. Mestres-Missé, A., Münte, T.F., Rodriguez-Fornells, A.: Mapping concrete and abstract meanings to new words using verbal contexts. Second Lang. Res. 30, 191–223 (2014)

    Article  Google Scholar 

  13. Sadoski, M., Kealy, W.A., Goetz, E.T., Paivio, A.: Concreteness and imagery effects in the written composition of definitions. J. Educ. Psychol. 89(3), 518–526 (1997). https://doi.org/10.1037/0022-0663.89.3.518

    Article  Google Scholar 

  14. de Groot, A.M.: Representational aspects of word imageability and word frequency as assessed through word association. J. Exp. Psychol. Learn. Mem. Cogn. 15(5), 824–845 (1989). https://doi.org/10.1037/0278-7393.15.5.824

    Article  Google Scholar 

  15. Rosa, P.A.D., Catrical, E., Canini, M., Vigliocco, G., Cappa, S.F.: The left inferior frontal gyrus: A neural crossroads between abstract and concrete knowledge. Neuroimage 175, 449–459 (2018). https://doi.org/10.1016/j.neuroimage.2018.04.021

    Article  Google Scholar 

  16. Paivio, A.: Dual coding theory. In: Broadbent, D.E., McGaugh, J.L., Mackintosh, N.J., Posner, M.I., Tulving, E., Weiskrantz L. (eds.) Mental Representations: A Dual Coding Approach, pp. 53–83. Oxford University Press, Oxford (1990). https://doi.org/10.1093/acprof:oso/9780195066661.003.0004

  17. Crutch, S.J.: Qualitatively different semantic representations for abstract and concrete words: further evidence from the semantic reading errors of deep dyslexic patients. Neurocase 12, 91–97 (2006). https://doi.org/10.1080/13554790500507172

    Article  Google Scholar 

  18. Myachykov, A., Fischer, M.H.: A hierarchical view of abstractness: grounded, embodied, and situated aspects. Phys. Life Rev. (2019). https://doi.org/10.1016/j.plrev.2019.04.005

    Article  Google Scholar 

  19. Pexman, P.M., Hargreaves, I.S., Edwards, J.D., Henry, L.C., Goodyear, B.G.: Neural correlates of concreteness in semantic categorization. J. Cogn. Neurosci. 19, 1407–1419 (2007). https://doi.org/10.1162/jocn.2007.19.8.1407

    Article  Google Scholar 

  20. Binder, J.R., Westbury, C.F., McKiernan, K.A., Possing, E.T., Medler, D.A.: Distinct brain systems for processing concrete and abstract concepts. J Cogn Neurosci. 7(6), 905–917 (2005). https://doi.org/10.1162/0898929054021102

    Article  Google Scholar 

  21. Dhond, R.P., Witzel, T., Dale, A.M., Halgren, E.: Spatiotemporal cortical dynamics underlying abstract and concrete word reading. Hum. Brain Mapp. 28(4), 355–362 (2007). https://doi.org/10.1002/hbm.20282

    Article  Google Scholar 

  22. Wang, J., Conder, J.A., Blitzer, D.N., Shinkareva, S.V.: Neural representation of abstract and concrete concepts: a meta-analysis of neuroimaging studies. Hum. Brain Mapp. 31, 1459–1468 (2010). https://doi.org/10.1002/hbm.20950

    Article  Google Scholar 

  23. Robson, H., Zahn, R., Keidel, J.L., Binney, R.J., Sage, K., Ralph, M.A.L.: The anterior temporal lobes support residual comprehension in Wernicke’s aphasia. Brain 137, 931–943 (2014). https://doi.org/10.1093/brain/awt373

    Article  Google Scholar 

  24. Pasquale, A., Rosa, D., Catricala, E., Vigliocco, G., Cappa, S.F.: Beyond the abstract–concrete dichotomy: mode of acquisition, concreteness, imageability, familiarity, age of acquisition, context availability, and abstractness norms for a set of 417 Italian words. Behav. Res. Meth. 42(4), 1042–1048 (2010). https://doi.org/10.3758/BRM.42.4.1042

    Article  Google Scholar 

  25. Kousta, S.T., Vigliocco, G., Vinson, D.P., Andrews, M., Del Campo, E.: The representation of abstract words: why emotion matters. Exp Psychol Gen. 140(1), 14–34 (2011). https://doi.org/10.1037/a0021446

    Article  Google Scholar 

  26. Paivio, A.: Dual coding theory, word abstractness, and emotion: a critical review of Kousta et al. (2011). J. Exp. Psychol. Gen. 142(1), 282–287 (2013). https://doi.org/10.1037/a0027004

    Article  Google Scholar 

  27. Bailey, D.J., Nessler, C., Berggren, K.N., Wambaugh, J.L.: An aphasia treatment for verbs with low concreteness: a pilot study. Am. J. Speech Lang. Pathol. 29(1), 299–318 (2020)

    Article  Google Scholar 

  28. Bolognesi, M., Burgers, C., Caselli, T.: On abstraction: decoupling conceptual concreteness and categorical specificity. Cogn. Process. 21, 365–381 (2020). https://doi.org/10.1007/s10339-020-00965-9

    Article  Google Scholar 

  29. Fellbaum, C.: WordNet: An Electronic Lexical Database. MIT Press (1998)

    Google Scholar 

  30. Frassinelli, D., Naumann, D., Utt, J., Schulte m Walde, S.: Contextual characteristics of concrete and abstract words. In Proceedings of the 12th International Conference on Computational Semantics, Montpellier (2017)

    Google Scholar 

  31. Naumann, D., Frassinelli, D., Schulte im Walde, S.: Quantitative semantic variation in the contexts of concrete and abstract words. In: Proceedings of the 7th Joint Conference on Lexical and Computational Semantics, New Orleans, LA, pp. 76–85 (2018)

    Google Scholar 

  32. Davies, M.: Expanding Horizons in historical linguistics with the 400 million word corpus of historical American English. Corpora 7, 121–157 (2012)

    Article  Google Scholar 

  33. Snefjella, B., Généreux, M., Kuperman, V.: Historical evolution of concrete and abstract language revisited. Behav. Res. 51, 1693–1705 (2019)

    Article  Google Scholar 

  34. Reilly, M., Desai, R.H.: Effects of semantic neighborhood density in abstract and concrete words. Cognition 169, 46–53 (2017). https://doi.org/10.1016/j.cognition.2017.08.004

    Article  Google Scholar 

  35. Feng, S., Cai, Z., Crossley, S.A., McNamara, D.S.: Simulating human ratings on word concreteness. In: FLAIRS Conference (2011)

    Google Scholar 

  36. Sadoski, M.: Resolving the effects of concreteness on interest, comprehension, and learning important ideas from text. Educ. Psychol. Rev. 13(3), 263–281 (2001)

    Article  Google Scholar 

  37. McNamara, D.S., Graesser, A.C., McCarthy, P.M., Cai, Z.: Automated Evaluation of Text and Discourse with Coh-Metrix. Cambridge University Press, Cambridge (2014)

    Book  Google Scholar 

  38. Coltheart, M.: The MRC psycholinguistic database. Q. J. Exp. Psychol. 33A, 497–505 (1981)

    Article  Google Scholar 

  39. Brysbaert, M., Warriner, A.B., Kuperman, V.: Concreteness ratings for 40 thousand generally known English word lemmas. Behav. Res. Methods 46(3), 904–911 (2014)

    Article  Google Scholar 

  40. Brysbaert, M., Stevens, M., De Deyne, S., Voorspoels, W., Storms, G.: Norms of age of acquisition and concreteness for 30,000 Dutch words. Acta Physiol. (Oxf) 150, 80–84 (2014). https://doi.org/10.1016/j.actpsy.2014.04.010

    Article  Google Scholar 

  41. Köper, M., Schulte im Walde, S.: Automatically generated affective norms of abstractness, arousal, imageability and valence for 350 000 German lemmas. In: Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016, pp. 2595–2598 (2016)

    Google Scholar 

  42. Solovyev, V.D., Ivanov, V.V., Akhtiamov, R.B.: Dictionary of abstract and concrete words of the Russian language: a methodology for creation and application. J. Res. Appl. Linguist. 10, 215–227 (2019)

    Google Scholar 

  43. Theijssen, D., Van Halteren, H., Boves, L., Oostdijk, N.: On the difficulty of making concreteness concrete. In: Computational Linguistics in the Netherlands, CLIN 21 (2011)

    Google Scholar 

  44. Charbonnier, J., Wartena, C.: Predicting the concreteness of German Words. In: Proceedings of the 5th Swiss Text Analytics Conference (SwissText) and 16th Conference on Natural Language Processing (KONVENS), CEUR-WS, vol. 2624 (2020). Paper 8

    Google Scholar 

  45. Solovyev, V.D., Bochkarev, V.V., Khristoforov, S.V.: Generation of a dictionary of abstract/concrete words by a multilayer neural network. J. Phys. Conf. Ser. 1680, 012046 (2020)

    Article  Google Scholar 

  46. Thompson, B., Lupyan, G.: Automatic estimation of lexical concreteness in 77 languages. In: The 40th Annual Conference of the Cognitive Science Society, pp. 1122–1127. Cognitive Science Society (2018)

    Google Scholar 

  47. Solovyev, V., Ivanov, V.: Automated compilation of a corpus-based dictionary and computing concreteness ratings of Russian. In: Karpov, A., Potapova, R. (eds.) Speech and Computer, SPECOM 2020. Lecture Notes in Computer Science, vol 12335, pp. 554–561. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-60276-5_53

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Acknowledgement

This research was financed by Russian Foundation for Basic Research, grant 19-07-00807.

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  1. Kazan Federal State University, Kazan, Russia

    Valery Solovyev

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  1. Valery Solovyev
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Correspondence to Valery Solovyev .

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  1. National Research Center "Kurchatov Institute", Moscow, Russia

    Boris M. Velichkovsky

  2. Institute of Higher Nervous Activity RAS, Moscow, Russia

    Pavel M. Balaban

  3. Institute for Advanced Brain Studies, Lomonosov Moscow State University, Moscow, Russia

    Vadim L. Ushakov

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Solovyev, V. (2021). Concreteness/Abstractness Concept: State of the Art. In: Velichkovsky, B.M., Balaban, P.M., Ushakov, V.L. (eds) Advances in Cognitive Research, Artificial Intelligence and Neuroinformatics. Intercognsci 2020. Advances in Intelligent Systems and Computing, vol 1358. Springer, Cham. https://doi.org/10.1007/978-3-030-71637-0_33

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