ABSTRACTIn this article we investigate structural differences between “literary” metaphors created by renowned poets and “nonliterary” ones imagined by non-professional authors from Katz et al.’s 1988 corpus. We provide data from quantitative narrative analyses of the altogether 464 metaphors on over 70 variables, including surface features like metaphor length, phonological features like sonority score, or syntactic-semantic features like sentence similarity. In a first computational study using machine learning tools we show that Katz et al.’s literary metaphors can be successfully discriminated (...) from their nonliterary ones on the basis of response measures, in particular the ratings for familiarity, ease of interpretation, semantic relatedness, and comprehensibility. A second computational study then shows that the classifier can reliably detect and predict between-group differences on the basis of five QNA features generalizing from a... (shrink)

The purpose of the article is to shed light on how experiences of sensory perceptions in the domains of vision, smell, taste, and touch are recast into text and discourse in the genre of wine reviews. Because of the alleged paucity of sensory vocabularies, in particular in the olfactory domain, it is of particular interest to investigate what resources language has to offer in order to describe those experiences. We show that the main resources are, on the one hand, words (...) evoking properties that are applicable cross-modally and properties of objects that range over more than one domain, and on the other, vivid imagery that compares the characteristics of the wine with people, buildings, animals, and the hustle and bustle of market places and other events. The second goal is to account for the construals of the meanings of the expressions used in the recontextualization into written discourse in the light of their apparent flexibility across the descriptions of the sensory experiences. In contrast to a large body of the literature on sensory meanings in language, we argue that the descriptors of properties such as sharp, soft, lemon, and cherry used to describe a wine's qualities across the sensory domains are not polysemous synesthetic metaphors, but monosemous synesthetic metonymizations, more precisely zone activations. With regard to the imagery used, the construals represented cover both similes, metaphorizations and metonymizations proper. (shrink)

This study seeks to clarify the nature of linguistic synesthesia using a lexical-conceptual account. Based on a lexical analysis of Mandarin synesthetic usages, we find that linguistic synesthesia maps the metaphorical meaning between two domains; and linguistic synesthetic mappings and conceptual metaphoric mappings have similar behaviors when sense modalities are treated as conceptual domains that contain a set of mappings constrained by Mapping Principles. This lexical-conceptual account is designed to capture the fact that linguistic synesthesia involves mapping between lexicalized concepts (...) of sensory properties, instead of the real-time sensory input that is processed in neurological synesthesia. The incorporation of a lexical semantic view with the framework of Conceptual Metaphor Theory not only offers a coherent and comprehensive account for the nature of linguistic synesthesia, but also handles aspects of linguistic synesthesia previously only accounted for by non-metaphorical accounts. These design features make this proposal the most comprehensive account to fit the current data. Furthermore, by showing linguistic synesthesia as a type of metaphor, our study strengthens the role of conceptual metaphors as the link between the perceived world and our conceptualization of that world. (shrink)

Two main goals of the emerging field of neurocognitive poetics are the use of more natural and ecologically valid stimuli, tasks and contexts and providing methods and models allowing to quantify distinctive features of verbal materials used in such tasks and contexts and their effects on readers responses. A natural key element of poetic language, metaphor, still is understudied insofar as relatively little empirical research looked at literary or poetic metaphors. An exception is Katz et al.’s corpus of 204 literary (...) metaphors by authors such as Shakespeare or Dylan Thomas, for which various rating data are available. We reanalyzed their corpus using a combination of quantitative narrative analysis, latent semantic analysis, and machine learning in order to identify relevant features of the metaphors that influenced the ratings. The combined application of computational tools sheds light on surface and affective-semantic features that co-determine the reception of poetic metaphors and successfully predicted the period of origin, authorship and goodness ratings of the metaphors. The present results can be used for generating quantitative hypotheses or selecting and matching verbal stimuli in empirical studies of literature and neurocognitive poetics. (shrink)