Linguistic Typology of Motion Events in Visual Narratives - Data and Publication

DOI

Languages use different strategies to encode motion. Some use particles or “satellites” to describe a path of motion (Satellite-framed or S-languages like English), while others typically use the main verb to convey the path information (Verb-framed or V-languages like French). We here ask: might this linguistic variation lead to differences in the way paths are depicted in visual narratives like comics? We analyzed a corpus of 85 comics originally created by speakers of S-languages (comics from the United States, China, Germany) and V-languages (France, Japan, Korea) for both their depictions of path segments (source, route, and goal) and the visual cues signaling these paths and manner information (e.g., motion lines and postures). Panels from S-languages depicted more path segments overall, especially routes, than those from V-languages, but panels from V-languages more often isolated path segments into their own panels. Additionally, comics from S-languages depicted more motion cues than those from V-languages, and this linguistic typology also interacted with panel framing. Despite these differences across typological groups, analysis of individual countries’ comics showed more nuanced variation than a simple S-V dichotomy. These findings suggest a possible influence of spoken language structure on depicting motion events in visual narratives and their sequencing.

Identifier
DOI https://doi.org/10.34894/F9UIDB
Related Identifier https://doi.org/10.1515/cogsem-2022-2013
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/F9UIDB
Provenance
Creator Cohn, Neil ORCID logo; Hacımusaoğlu, Irmak ORCID logo
Publisher DataverseNL
Contributor Cohn, Neil
Publication Year 2023
Funding Reference European Research Council, 850975
Rights CC-BY-4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact Cohn, Neil (Tilburg University, Tilburg School of Humanities and Digital Sciences, Department of Cognition and Communication)
Representation
Resource Type Corpus analysis; Dataset
Format application/pdf; text/csv
Size 1637182; 170589; 15435
Version 1.0
Discipline Basic Biological and Medical Research; Biology; Humanities; Life Sciences; Linguistics; Omics