Athec: A Python Library for Computational Aesthetic Analysis of Visual Media in Social Science Research

Computational Communication Research, Forthcoming

32 Pages Posted: 9 Aug 2021 Last revised: 24 Aug 2021

Date Written: August 1, 2021

Abstract

Visual aesthetics are related to a broad range of communication and psychological outcomes, yet the tools of computational aesthetic analysis are not widely available in the community of social science scholars. This article addresses this gap and provides a tutorial for social scientists to measure a broad range of hand-crafted aesthetic attributes of visual media, such as colorfulness and visual complexity. It introduces Athec, a Python library developed for computational aesthetic analysis in social science research, which can be readily applied by future researchers. In addition, a case study applies Athec to compare the visual aesthetics of Instagram posts from the two candidates in the 2016 US presidential election, Hillary Clinton and Donald Trump, showing how amateurishness and authenticity are reflected in politicians’ visual messages. With tools of computational aesthetic analysis, communication researchers can better understand the antecedents and outcomes of visual aesthetics beyond the content of visual media.

Keywords: computational aesthetics, computer vision, aesthetic analysis, image feature, visual complexity, authenticity

Suggested Citation

Peng, Yilang, Athec: A Python Library for Computational Aesthetic Analysis of Visual Media in Social Science Research (August 1, 2021). Computational Communication Research, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3899662 or http://dx.doi.org/10.2139/ssrn.3899662

Yilang Peng (Contact Author)

University of Georgia ( email )

Athens, GA 30602-6254
United States

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