STUDYING 'LIVE' CROSS-PLATFORM CIRCULATION OF IMAGES WITH A COMPUTER VISION API: AN EXPERIMENT BASED ON A SPORTS MEDIA EVENTd'Andréa, Carlos Frederico de Brito (Federal University of Minas Gerais, Brazil) <carlosfbd@gmail.com>

Abstract

Considering the importance of cross-platform circulation of web contents for digital methods-oriented research, in this study we aim to expand the types of digital objects used as ‘traffic tags’ by focusing on static images as traces of online associations. We pursue this goal through a methodological experiment with Google Cloud Vision API, a computing framework for visual content analysis. Its Web Detection module pairs typical computer vision operations with Google’s search mechanism, partly performing as a more specialized batch reverse image search engine. This feature thus allows to potentially retrieve images’ spread across the web. We discuss the implications of this non-verbal methodological approach by tracking the 'live' cross-platform circulation of images shared on Twitter in the context of 2018 FIFA World Cup Final Draw ceremony, held on December 2017. Following a novel methodological protocol, we ran several iterations of Vision API processing, thus generating a time series of URLs pointing to pages in which images matching the ones being processed were found. The study analyses in depth the circulation of four popular images about the broadcasted media event, observing their ‘live’ spreading dynamics as well as the computer vision API performance. Among the findings, we point out the adoption of images as 'traffic tags' for cross-platform analysis as a promising approach to study web circulation beyond language barriers and mainstream platforms. Also, we find relevant data to discuss the specificities of the API’s algorithms and its opacity as inherent issues of the digital methods approach.