COLOR ASSOCIATIONS IN ABSTRACT SEMANTIC DOMAINS

Color Associations in Abstract Semantic Domains

Douglas Guilbeaulta*, Ethan O. Nadlerb,c, Mark Chud, Donald Ruggiero Lo Sardo e,f, Aabir Abubaker Karg, h, Bhargav Srinivasa Desikang,h

a The Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA b Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, USA c Department of Physics, Stanford University, USA d School of the Arts, Columbia University, USA e Section for Medical Information Management, CeMSIIS, Medical University of Vienna, Austria f Complexity Science Hub Vienna, Austria g Division of the Social Sciences, University of Chicago, USA h Knowledge Lab, University of Chicago, USA

*Corresponding author: Douglas Guilbeault ([email protected])

Forthcoming in Cognition (2020).

Keywords: | lexical semantics | multimodal cognition | machine learning | abstraction

1 COLOR ASSOCIATIONS IN ABSTRACT SEMANTIC DOMAINS

Color Associations in Abstract Semantic Domains

Abstract

The embodied cognition paradigm has stimulated ongoing debate about whether sensory data – including color – contributes to the semantic structure of abstract concepts. Recent uses of linguistic data in the study of embodied cognition have been focused on textual corpora, which largely precludes the direct analysis of sensory information. Here, we develop an automated approach to multimodal that detects associations between words based on the color distributions of their Google Image search results. Crucially, we measure color using a transformation of colorspace that closely resembles human color . We find that words in the abstract domains of academic disciplines, emotions, and music genres, cluster in a statistically significant fashion according to their color distributions. Furthermore, we use the lexical ontology WordNet and crowdsourced human judgments to show that this clustering reflects non-arbitrary semantic structure, consistent with metaphor-based accounts of embodied cognition. In particular, we find that images corresponding to more abstract words exhibit higher variability in colorspace, and semantically similar words have more similar color distributions. Strikingly, we show that color associations often reflect shared affective dimensions between abstract domains, thus revealing patterns of aesthetic coherence in everyday language. We argue that these findings provide a novel way to synthesize metaphor-based and affect-based accounts of embodied semantics.

1. Introduction

Color has been harnessed as a means of communication throughout human history, as evidenced by its use in painting, poetry, fashion, architecture, and (Lakoff & Turner, 1989; Riley, 1995; Labrecque & Milne, 2012). Indeed, recent work shows that color can prime a range of attentional, emotional, and interpretive responses (Hill & Barton, 2005; Mehta & Zhu, 2009; Labrecque & Milne, 2012; Elliot & Maier, 2014). Color is also frequently used in linguistic metaphors to describe concepts across varying levels of abstraction, including those that lack direct visible referents (e.g., “I could play the and then not be anymore” — B.B. King) (Lakoff & Turner, 1989; Winter et al., 2018; Winter, 2019). A number of studies have found that linguistic metaphors can activate neurocognitive processes similar to those involved in forms of synaesthesia that ascribe to letters or numbers (Marks, 1982; O’Dowd et al., 2019). These findings are consistent with theories of multimodal cognition which argue that the metaphorical use of sensory data in everyday language indicates that sensory data plays a key r