New machine learning methods demonstrate the existence of a human stylome

Van Halteren, Hans; Baayen, R. Harald; Tweedie, Fiona; Haverkort, Marco; Neijt, Anneke

doi:10.1080/09296170500055350

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New machine learning methods demonstrate the existence of a human stylome

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Baayen, R. Harald
Pioneer, external;
Other Research, MPI for Psycholinguistics, Max Planck Society;

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Citation

Van Halteren, H., Baayen, R. H., Tweedie, F., Haverkort, M., & Neijt, A. (2005). New machine learning methods demonstrate the existence of a human stylome. Journal of Quantitative Linguistics, 12(1), 65-77. doi:10.1080/09296170500055350.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-1CB6-5

Abstract

Earlier research has shown that established authors can be distinguished by measuring specific properties of their writings, their stylome as it were. Here, we examine writings of less experienced authors. We succeed in distinguishing between these authors with a very high probability, which implies that a stylome exists even in the general population. However, the number of traits needed for so successful a distinction is an order of magnitude larger than assumed so far. Furthermore, traits referring to syntactic patterns prove less distinctive than traits referring to vocabulary, but much more distinctive than expected on the basis of current generativist theories of language learning.