Detecting Cultural Differences in News Video Thumbnails via Computational Aesthetics

TL;DR

This paper introduces a two-step computational approach to identify cultural differences in news video thumbnails by analyzing aesthetic features, revealing distinct stylistic preferences between Chinese and U.S. channels related to COVID-19 and Ukraine conflicts.

Contribution

The study presents a novel method combining content-based clustering with aesthetic feature comparison to detect cultural stylistic differences in news thumbnails.

Findings

Chinese thumbnails are less formal and more candid.

U.S. thumbnails are more deliberate, proper, and detailed.

Distinct aesthetic patterns reflect cultural preferences.

Abstract

We propose a two-step approach for detecting differences in the style of images across sources of differing cultural affinity, where images are first clustered into finer visual themes based on content before their aesthetic features are compared. We test this approach on 2,400 YouTube video thumbnails taken equally from two U.S. and two Chinese YouTube channels, and relating equally to COVID-19 and the Ukraine conflict. Our results suggest that while Chinese thumbnails are less formal and more candid, U.S. channels tend to use more deliberate, proper photographs as thumbnails. In particular, U.S. thumbnails are less colorful, more saturated, darker, more finely detailed, less symmetric, sparser, less varied, and more up close and personal than Chinese thumbnails. We suggest that most of these differences reflect cultural preferences, and that our methods and observations can serve as a baseline against which suspected visual propaganda can be computed and compared.