Abstract

How do drawings—ranging from detailed illustrations to schematic diagrams—reliably convey meaning? Do viewers understand drawings based on how strongly they resemble an entity (i.e., as images) or based on socially mediated conventions (i.e., as symbols)? Here we evaluate a cognitive account of pictorial meaning in which visual and social information jointly support visual communication. Pairs of participants used drawings to repeatedly communicate the identity of a target object among multiple distractor objects. We manipulated social cues across three experiments and a full replication, finding that participants developed object-specific and interaction-specific strategies for communicating more efficiently over time, beyond what task practice or a resemblance-based account alone could explain. Leveraging model-based image analyses and crowdsourced annotations, we further determined that drawings did not drift toward “arbitrariness,” as predicted by a pure convention-based account, but preserved visually diagnostic features. Taken together, these findings advance psychological theories of how successful graphical conventions emerge.

Drawings can vary in abstraction while still being meaningful. Here, the authors leverage a two-player drawing game to evaluate a cognitive account of pictorial meaning in which both visual and social information jointly support visual communication.

Details

Title
Visual resemblance and interaction history jointly constrain pictorial meaning
Author
Hawkins, Robert D. 1   VIAFID ORCID Logo  ; Sano, Megumi 2 ; Goodman, Noah D. 3 ; Fan, Judith E. 4   VIAFID ORCID Logo 

 Stanford University, Department of Psychology, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956); Princeton University, Department of Psychology, Princeton, USA (GRID:grid.16750.35) (ISNI:0000 0001 2097 5006) 
 Stanford University, Department of Psychology, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956) 
 Stanford University, Department of Psychology, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956); Stanford University, Department of Computer Science, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956) 
 Stanford University, Department of Psychology, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956); University of California, Department of Psychology, San Diego, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) 
Pages
2199
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2802198376
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.