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Mental Lexicon Growth Modelling Reveals the Multiplexity of the English Language

  • Massimo Stella
  • Markus Brede
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 644)

Abstract

In this work we extend previous analyses of linguistic networks by adopting a multi-layer network framework for modelling the human mental lexicon, i.e. an abstract mental repository where words and concepts are stored together with their linguistic patterns. Across a three-layer linguistic multiplex, we model English words as nodes and connect them according to (i) phonological similarities, (ii) synonym relationships and (iii) free word associations. Our main aim is to exploit this multi-layered structure to explore the influence of phonological and semantic relationships on lexicon assembly over time. We propose a model of lexicon growth which is driven by the phonological layer: words are suggested according to different orderings of insertion (e.g. shorter word length, highest frequency, semantic multiplex features) and accepted or rejected subject to constraints. We then measure times of network assembly and compare these to empirical data about the age of acquisition of words. In agreement with empirical studies in psycholinguistics, our results provide quantitative evidence for the hypothesis that word acquisition is driven by features at multiple levels of organisation within language.

Keywords

Degree Distribution Semantic Network Phonological Similarity Mental Lexicon High Frequency Word 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

MS acknowledges the DTC in Complex Systems Simulation, University of Southampton for financial support. The authors acknowledge Dr. Srinandan Dasmahapatra, Nicole Beckage and the reviewers for providing insightful comments.

References

  1. 1.
    Aitchison, J.: Words in the Mind: An Introduction to the Mental Lexicon. Wiley (2012)Google Scholar
  2. 2.
    Baronchelli, A., Ferrer-i Cancho, R., Pastor-Satorras, R., Chater, N., Christiansen, M.H.: Trends Cogn. Sci. 17(7), 348 (2013)Google Scholar
  3. 3.
    Beckage, N.M., Colunga, E.: Towards a Theoretical Framework of Analyzing Complex Linguistic Networks. In: Mehler, A., Blanchard, P., Job, B., Banisch, S. (eds.) Springer (2015)Google Scholar
  4. 4.
    Vitevitch, M.S.: J. Speech Lang. Hear. Res. 51(2), 408 (2008)CrossRefGoogle Scholar
  5. 5.
    Motter, A.E., de Moura, A.P., Lai, Y.C., Dasgupta, P.: Phys. Rev. E 65(6), 065102 (2002)CrossRefGoogle Scholar
  6. 6.
    Sigman, M., Cecchi, G.A.: PNAS 99(3), 1742 (2002)CrossRefGoogle Scholar
  7. 7.
    Collins, A.M., Loftus, E.F.: Psychol. Rev. 82(6), 407 (1975)CrossRefGoogle Scholar
  8. 8.
    de Deyne, S., Storms, G.: Behav. Res. Methods 40(1), 213 (2008)Google Scholar
  9. 9.
    Steyvers, M., Tenenbaum, J.B.: Cogn. Sci. 29(1), 41 (2005)CrossRefGoogle Scholar
  10. 10.
    Vitevitch, M.S., Chan, K.Y., Goldstein, R.: Cogn. Psychol. 68, 1 (2014)CrossRefGoogle Scholar
  11. 11.
    Stella, M., Brede, M.: J. Stat. Mech. 2015, P05006 (2015)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Stella, M., Brede, M.: Accepted in Lecture Notes in Computer Science (2015)Google Scholar
  13. 13.
    Battiston, F., Nicosia, V., Latora, V.: Phys. Rev. E 89(3), 032804 (2014)CrossRefGoogle Scholar
  14. 14.
    Boccaletti, S., Bianconi, G., Criado, R., Del Genio, C.I., Gómez-Gardeñes, J., Romance, M., Sendina-Nadal, I., Wang, Z., Zanin, M.: Phys. Rep. 544(1), 1 (2014)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Kuperman, V., Stadthagen-Gonzalez, H., Brysbaert, M.: Behav. Res. Methods 44(4), 978 (2012)Google Scholar
  16. 16.
    Kiss, G., Armstrong, C.A., Milroy, R.: Medical Research Council (1972)Google Scholar
  17. 17.
    Miller, G., Fellbaum, C., Tengi, R., Wakefield, P., Langone, H., Haskell, B.: WordNet. MIT Press, Cambridge (1998)Google Scholar
  18. 18.
  19. 19.
    Barbaresi, A.: Language-classified open subtitles (laclos). Ph.D. thesis, BBAW (2014)Google Scholar
  20. 20.
    Newman, M.: Networks: an Introduction. Oxford University Press (2010)Google Scholar
  21. 21.
    Ferguson, C.A., Farwell, C.B: Language. pp. 419–439 (1975)Google Scholar
  22. 22.
    Schwartz, R.G., Leonard, L.B.: J. Child Lang. 9(02), 319 (1982)CrossRefGoogle Scholar
  23. 23.
    Stoel-Gammon, C., Cooper, J.A.: J. Child Lang. 11(02), 247 (1984)CrossRefGoogle Scholar
  24. 24.
    Hoff, E., Core, C., Bridges, K.: J. Child Lang. 35(04), 903 (2008)CrossRefGoogle Scholar
  25. 25.
    Wiethan, F.M., Nóro, L.A., Mota, H.B.: CoDAS, vol. 4, pp. 260–264. SciELO, Brasil (2014)Google Scholar
  26. 26.
    Beckage, N.M., Aguilar, A., Colunga, E.: Proceedings of CogSci2015 (2015)Google Scholar
  27. 27.
    Moore, D.S., McCabe, G.P.: Introduction to the Practice of Statistics. WH Freeman/Times Books/Henry Holt & Co (1989)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Institute for Complex Systems SimulationUniversity of SouthamptonSouthamptonUK

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