Crowdsourcing Image Schemas

Authors

Dagmar Gromann, Technische Universität Dresden
Jamie C. Macbeth, Smith CollegeFollow

Document Type

Conference Proceeding

Publication Date

1-1-2019

Publication Title

CEUR Workshop Proceedings

Abstract

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.

Keywords

Cognitive linguistics, Crowdsourcing, Image schema, Natural language annotation, Natural language understanding

Volume

2347

ISSN

16130073

Rights

Copyright © 2018 for the individual papers by the papers' authors.

Comments

Archived as published.

Recommended Citation

Gromann, Dagmar and Macbeth, Jamie C., "Crowdsourcing Image Schemas" (2019). Computer Science: Faculty Publications, Smith College, Northampton, MA.
https://scholarworks.smith.edu/csc_facpubs/161