CEUR Workshop Proceedings
With their potential to map experiental structures from the sensorimotor to the abstract cognitive realm, image schemas are believed to provide an embodied grounding to our cognitive conceptual system, including natural language. Few empirical studies have evaluated humans’ intuitive understanding of image schemas or the coherence of image-schematic annotations of natural language. In this paper we present the results of a human-subjects study in which 100 participants annotate 12 simple English sentences with one or more image schemas. We find that human subjects recruited from a crowdsourcing platform can understand image schema descriptions and use them to perform annotations of texts, but also that in many cases multiple image schema annotations apply to the same simple sentence, a phenomenon we call image schema collocations. This study carries implications both for methodologies of future studies of image schemas, and for the inexpensive and efficient creation of large text corpora with image schema annotations.
Cognitive linguistics, Crowdsourcing, Image schema, Natural language annotation, Natural language understanding
Copyright © 2018 for the individual papers by the papers' authors.
Gromann, Dagmar and Macbeth, Jamie C., "Crowdsourcing Image Schemas" (2019). Computer Science: Faculty Publications, Smith College, Northampton, MA.