Running through the Who, Where, and When - Data and Publication

DOI

Understanding visual narratives requires readers to track dimensions of time, spatial location, and characters across a sequence. Previous work has found situational changes across adjacent panels differ cross-culturally, but few works have examined such situational dimensions across extended sequences. We therefore investigated situational ‘runs’—uninterrupted sequences of the situational dimensions (time, space, characters)—in a corpus of 300+ annotated comics from the United States, Europe, and Asia. We compared runs’ proportion and average lengths and found that across books, semantic information changed frequently and run length correlated with proportion. Yet, cross-cultural patterns arose, with American and European comics using more continuous runs than Asian comics. American and European comics also used more and longer temporal and character continuity, while Asian comics used more spatial continuity. These findings raise questions about comprehenders’ processing strategies of visual narratives across cultures and how general frameworks of visual narrative comprehension account for variations in situational (dis)continuity.

This is an analysis of the data from the Visual Language Research Corpus (VLRC):
https://doi.org/10.34894/LWMZ7G.

Identifier
DOI https://doi.org/10.34894/2GGNHW
Related Identifier https://doi.org/10.1080/0163853X.2022.2106402
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/2GGNHW
Provenance
Creator Cohn, Neil ORCID logo; Klomberg, Bien ORCID logo; Hacımusaoğlu, Irmak ORCID logo
Publisher DataverseNL
Contributor Cohn, Neil; DataverseNL
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 2783039; 178810; 956; 1358; 69783; 73629; 148292; 53728
Version 1.0
Discipline Basic Biological and Medical Research; Biology; Humanities; Life Sciences; Linguistics; Omics