This Figure shows the estimated probability of being ‚literary‘ (i.e., having been created by a professional author) for three examples selected from a set of 464 metaphors (cf. Katz et al., 1988).
The estimates are based on a recent machine learning assisted ACTA (cf. Jacobs & Kinder, 2017, 2018).
Among other features, a metaphor’s sonority score (i.e., its sound beauty; cf. example VII), its semantic relatedness to metaphors created by other poets, its surprise potential or its length (in words) play a role for judging its ‚literariness‘.
Jacobs, A. M., & Kinder, A. (2017). The brain is the prisoner of thought: A machine-learning assisted quantitative narrative analysis of literary metaphors for use in Neurocognitive Poetics. Metaphor and Symbol, 32:3, 139-160 https://doi.org/
Jacobs, A. M., & Kinder, A. (2018). What makes a metaphor literary? Answers from two computational studies, Metaphor and Symbol, 33:2, 85-100, DOI: 10.1080/10926488.2018.1434943 https://www.researchgate.net/publication/324764928
Katz, A., Paivio, A., Marschark, M., & Clark, J. (1988). Norms for 204 literary and 260 non-literary metaphors on psychological dimensions. Metaphor and Symbolic Activity, 3(4), 191–214.