Hidden messages: computer vision and visual communication

• In Event: Image and Video as Data

Abstract

Political communication is a central element of several political dynamics. Its visual component is crucial in understanding the origin, characteristics and consequences of the messages sent between political figures, media and citizens. However, visual features have been largely overlooked in Political Science. In this project, I implement computer vision and image retrieval techniques to measure and understand messages conveyed in pictures: more specifically, conflict and violence in protests. This project focuses on the images published in news regarding the Black Lives Matter movement (BLMM). The main objective of this paper is to identify and measure a latent scale of conflict in the images used to communicate information about the BLMM using visual analysis and both unsupervised and supervised machine learning tools. Identifying and understanding visual stimuli is crucial for a proper understanding of the messages that ultimately shape citizens' political attitudes and behavior.

Author

• Michelle Torres, Washington University in St. Louis