A Character Recognition Tool for Automatic Detection of Social Characters in Visual Media Content

Abstract

Content analysis is the go-to method for understanding how social characters, such as public figures or movie characters, are portrayed in media messages. It is an indispensable method to investigate character-related media processes and effects. However, conducting large-scale content-analytic studies is a taxing and expensive endeavor that requires hours of coder training and incurs substantial costs. This problem is particularly acute for video-based media, where coders often have to take extensive time and energy to watch and interpret dynamic content. Here we present a Character-Recognition-Tool (CRT) that enables communication scholars to quickly process large amounts of video data to identify occurrences of specific predefined characters using facial recognition and matching. This paper presents the CRT and provides evidence for its validity. The CRT can automate the coding process of onscreen characters while following recommendations that computational tools be scalable, adaptable for novice programmers, and open source to allow for replication.

Keywords: computer vision, computational communication, content analysis, face recognition, media