The advertising-driven business models of social media platforms increasingly depend on automation. The technologies used by platforms are rapidly advancing, and include ‘machine vision’ systems that automatically classify faces, expressions, objects, and brand logos in images. The results are used to provide targeted content to users, often without their knowledge and without sufficient public oversight. Using a novel combination of computational and cultural research methods, this project aims to: examine how machine vision works in platforms like Instagram; explore its role in everyday visual contexts through qualitative case studies of festivals, food, and lifestyle sports; and improve public understanding of machine vision systems.
DMRC research programs
This project contributes to the research within the following DMRC research programs:
Transforming Media Industries | Digital Publics | Computational Communication & Culture
- Professor Daniel Angus
- Professor Jean Burgess
- Dr Nicholas Carah, University of Queensland
- ARC Discovery Project (2020)
Connected and consuming: applying a deep learning algorithm to quantify alcoholic beverage prevalence in user-generated instagram images
Norman, Thomas, Bonela, Abraham Albert, He, Zhen, Angus, Daniel, Carah, Nicholas, and Kuntsche, Emmanuel; Drugs: Education, Prevention and Policy (2021)
View on eprints.
Algorithmic brand culture: participatory labour, machine learning and branding on social media
Caras, Nicholas and Angus, Daniel; Media Culture & Society (2018)