DMRC Monthly Methods Workshop: Machine-learning methods for supporting qualitative analysis of digital images

This workshop will introduce participants to a novel computational method for supporting the analysis of large image collections, with a specific focus on images obtained from Instagram and Facebook. This novel method is an outcome of the ARC Discovery Project “Using machine vision to explore Instagram’s everyday promotional cultures”.  The workshop will provide an introduction to the machine learning methods involved in processing these images for a non-technical audience, and a hands-on session where participants will be able to trial the methods on their own computer using a pre-loaded dataset. Participants are not required to have any previous experience with advanced computational methods. Participants are encouraged to preload Docker ( on their computer ahead of the workshop.

Dr Daniel Angus is Associate Professor of Digital Communication in the School of Communication, and leader of the Computational Communication and Culture program in QUT’s Digital Media Research Centre. His research focuses on the development and application of visual computational analysis methods in communication and media studies, with a specific focus on conversation and social media data. His novel computational methods have improved our understanding of the nature of communication in medical consultations, conversations in aged care settings, television broadcast, social media, and newspaper reporting. Daniel is an Associate Investigator in the ARC Centre of Excellence for the Dynamics of Language, and the ARC Centre of Excellence for Automated Decision Making & Society, and a Chief Investigator on the ARC Discovery Projects, Evaluating the Challenge of ‘Fake News’ and Other Malinformation, and Using machine vision to explore Instagram’s everyday promotional cultures.

RSVP by emailing:

*In person only event, you will be required to a scan a QR code on arrival.