A Computer Vision Methodology to Predict Brand Personality from Image Features

Bibliographic Data

ID21422796
AuthorsYilang Peng (0000-0001-7711-9518, University of Georgia, Athens, Georgia, USA), Taylor Jing Wen (0000-0002-6967-1617, University of South Carolina, Columbia, South Carolina, USA, corresponding author), Jing Yang (0009-0004-1715-4513, Loyola University Chicago, Chicago, Illinois, USA)
Year2024
Volume53
Issue4
Pages626-638
Publication date2024-08-07
Open AccessNo
TypeARTICLE
VenueJournal of Advertising (JOURNAL)
Journal identifiersISSN: 0091-3367 • E-ISSN: 1557-7805
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/00913367.2023.2250842
OpenAlexW4386923463
LanguageEN
Citations received2
References cited44

Using the computer vision method, this study proposes an analytical model of visual aesthetics for brand communication and analyzes the effects of visual features (i.e., colors and visual complexity) on brand personality. This study illustrates a four-step procedure correlating computationally coded visual attributes with human ratings of perceived brand personality. This study has important methodological implications for advertising researchers and practitioners

Advertising · Brand Image · Business · Cognitive psychology · Personality · Aesthetic Perception and Analysis · Color perception and design · Computer Science · Consumer Behavior in Brand Consumption and Identification · Psychology · Social Psychology

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