An AI Method to Score Celebrity Visual Potential from Human Faces

88 Pages Posted: 8 Apr 2022 Last revised: 25 Apr 2022

See all articles by Xiaohang Feng

Xiaohang Feng

Carnegie Mellon University

Shunyuan Zhang

Harvard University - Business School (HBS); Harvard University

Xiao Liu

New York University (NYU) - Leonard N. Stern School of Business

Kannan Srinivasan

Carnegie Mellon University - David A. Tepper School of Business

Cait Poynor Lamberton

University of Pennsylvania

Date Written: May 1, 2021

Abstract

Celebrities have extraordinary abilities to attract and influence others. Predicting celebrity visual potential is important in the domains of business, politics, media, and entertainment. Can we use human faces to predict celebrity visual potential? If so, which facial features have the most impact on celebrity visual potential? We develop a three-step empirical framework that leverages computer vision techniques to predict celebrity visual potential from face images. In the prediction step, we optimize a ResNet-50 deep learning model on a large dataset of 6,000 celebrity images and 6,000 non-celebrity images and achieve 95.92% accuracy. In the interpretation step, we draw on psychology, economics, and behavioral marketing literature to select 11 interpretable facial features (e.g., width-to-height ratio). We calculate the direction and strength of the feature’s correlation with celebrity visual potential. We find that the facial width-to-height ratio, babyfaceness, and thin jaw contribute negatively to celebrity visual potential while sexual dimorphism, dark skin color, and large eyes contribute positively. In the mechanism step, we compare the interpretation results with extant theoretical relationships between facial features and celebrity visual potential, with personality traits as mediators. Contradicting theoretical predictions, we discover a negative correlation between averageness and celebrity visual potential. We demonstrate the generalizability of our results to media/entertainment and business domains. We also conduct experiments to compare our model-predicted scores with human-rated scores on celebrity-visual potential for further validation.

Keywords: Celebrity Visual Potential, Facial Features, Personality Traits, Deep Learning, XAI

Suggested Citation

Feng, Xiaohang and Zhang, Shunyuan and Liu, Xiao and Srinivasan, Kannan and Lamberton, Cait Poynor, An AI Method to Score Celebrity Visual Potential from Human Faces (May 1, 2021). Available at SSRN: https://ssrn.com/abstract=4067555 or http://dx.doi.org/10.2139/ssrn.4067555

Xiaohang Feng (Contact Author)

Carnegie Mellon University ( email )

Pittsburgh, PA 15213-3890
United States

Shunyuan Zhang

Harvard University - Business School (HBS) ( email )

Soldiers Field Road
Morgan Hall
Boston, MA 02163
United States

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

Xiao Liu

New York University (NYU) - Leonard N. Stern School of Business ( email )

Suite 9-160
New York, NY
United States

Kannan Srinivasan

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States

Cait Poynor Lamberton

University of Pennsylvania ( email )

Marketing Department
Philadelphia, PA
United States

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