Visual Listening In: Extracting Brand Image Portrayed on Social Media

53 Pages Posted: 6 Jun 2017 Last revised: 29 Feb 2020

See all articles by Liu Liu

Liu Liu

University of Colorado at Boulder - Leeds School of Business

Daria Dzyabura

New economic school

Natalie Mizik

University of Washington

Date Written: Feb 27, 2020

Abstract

We propose a “visual listening in” approach (i.e., mining visual content posted by users) to measure how brands are portrayed on social media. Using a deep-learning framework, we develop BrandImageNet, a multi-label convolutional neural network model, to predict the presence of perceptual brand attributes in the images that consumers post online. We validate model performance using human judges, and we find a high degree of agreement between our model and human evaluations of images. We apply the BrandImageNet model to brand-related images posted on social media and compute a brand-portrayal metric based on model predictions for 56 national brands in the apparel and beverages categories. We find a strong link between brand portrayal in consumer-created images and consumer brand perceptions collected through survey tools. Images are close to surpassing text as the medium of choice for online conversations. They convey rich information about the consumption experience, attitudes, and feelings of the user. We show that valuable insights can be efficiently extracted from consumer-created images. Firms can use the BrandImageNet model to automatically monitor in real time their brand portrayal and better understand consumer brand perceptions and attitudes toward theirs and competitors’ brands.

Keywords: Social Media, Visual Marketing, Brand Perceptions, Computer Vision, Machine Learning, Deep Learning, Transfer Learning, Big Data

Suggested Citation

Liu, Liu and Dzyabura, Daria and Mizik, Natalie, Visual Listening In: Extracting Brand Image Portrayed on Social Media (Feb 27, 2020). Available at SSRN: https://ssrn.com/abstract=2978805 or http://dx.doi.org/10.2139/ssrn.2978805

Liu Liu (Contact Author)

University of Colorado at Boulder - Leeds School of Business ( email )

Boulder, CO 80309-0419
United States

HOME PAGE: http://www.colorado.edu/business/liu-liu

Daria Dzyabura

New economic school ( email )

100A Novaya Street
Moscow, Skolkovo 143026
Russia

Natalie Mizik

University of Washington ( email )

Seattle, WA 98195
United States

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