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Doctor of Philosophy (Swinburne Institute of Technology)
Prof. Daniel Angus is 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 has been involved in computer science research for 20 years and he contributes regularly to media and industry on the impact of technology on society. Daniel received a BS/BE double degree in research and development, and electronics and computer systems, and the PhD degree in computer science from Swinburne University of Technology, in 2004 and 2008, respectively. Between 2008 and 2018 he worked in a number of roles at The University of Queensland, leading collaborative research at the intersection of computer science, design, communication, linguistics, and journalism. He 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.
Additional information
Daniel is a co-convenor of the Brisbane chapter of the worldwide Hacks/Hackers movement. Hacks/Hackers brings technologists and journalists together to explore opportunities and challenges at the boundary of these disciplines. Prior to, and over the course of his academic career Daniel has worked in a number of rewarding consultancy and full-time professional roles. Daniel has worked in:
- standards testing and Engineering (automotive / white goods / built environment);
- automated portfolio management in the finance sector;
- data analytics for the healthcare sector; and,
- communication analytics for the minerals and natural resource sector.
- Angus, D., Rintel, S. & Wiles, J. (2013). Making sense of big text: a visual-first approach for analysing text data using Leximancer and Discursis. International Journal of Social Research Methodology: Theory and Practice, 16(3), 261–267. https://eprints.qut.edu.au/125098
- Angus, D. & Wiles, J. (2018). Social semantic networks: Measuring topic management in discourse using a pyramid of conceptual recurrence metrics. Chaos, 28(8), 1–12. https://eprints.qut.edu.au/125096
- Carah, N. & Angus, D. (2018). Algorithmic brand culture: participatory labour, machine learning and branding on social media. Media, Culture and Society, 40(2), 178–194. https://eprints.qut.edu.au/125111
- Angus, D., Fitzgerald, R., Atay, C. & Wiles, J. (2016). Using visual text analytics to examine broadcast interviewing. Discourse, Context and Media, 11, 38–49. https://eprints.qut.edu.au/125093
- Angus, D., Yu, Y., Vrbik, P., Back, A. & Wiles, J. (2018). PauseCode: Computational conversation timing analysis. Proceedings of the 4th International Workshop on Multimodal Analyses Enabling Artificial Agents in Human-Machine Interaction, 43–47. https://eprints.qut.edu.au/125109
- Angus, D., Smith, A. & Wiles, J. (2012). Conceptual recurrence plots: Revealing patterns in human discourse. IEEE Transactions on Visualization and Computer Graphics, 18(6), 988–997. https://eprints.qut.edu.au/125106
- Angus, D., Watson, B., Smith, A., Gallois, C. & Wiles, J. (2012). Visualising conversation structure across time: Insights into effective doctor-patient consultations. PLoS One, 7(6), 1–12. https://eprints.qut.edu.au/125115
- Byrne, L., Angus, D. & Wiles, J. (2019). Figurative frames: A critical vocabulary for images in information visualization. Information Visualization, 18(1), 45–67. https://eprints.qut.edu.au/125114
- Angus, D., Smith, A. & Wiles, J. (2012). Human communication as coupled time series: Quantifying multi-participant recurrence. IEEE Transactions on Audio, Speech and Language Processing, 20(6), 1795–1807. https://eprints.qut.edu.au/125105
- Baker, R., Angus, D., Conway-Smith, E., Baker, K., Gallois, C., Smith, A., Wiles, J. & Chenery, H. (2015). Visualising conversations between care home staff and residents with dementia. Ageing and Society, 35(2), 270–297. https://eprints.qut.edu.au/125095
- Title
- Using Machine Vision to Explore Instagram's Everyday Promotional Cultures
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP200100519
- Start year
- 2020
- Keywords
- Title
- Evaluating the Challenge of 'Fake News' and Other Malinformation
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP200101317
- Start year
- 2020
- Keywords
- Computational approaches and tools for critical simulation of Convolutional Neural Networks in visual social media
PhD, Principal Supervisor
Other supervisors: Professor Jean Burgess - No tool is a box: Unpacking embedded knowledge to address tool/language barriers
PhD, Principal Supervisor
Other supervisors: Professor Axel Bruns - Imaginary Containers and Imaginary Coins: e-publishing using smart contracts
PhD, Principal Supervisor
Other supervisors: Professor Patrik Wikstrom - MY DIGITAL 'FRIEND': DESIGN CONSIDERATIONS WHEN DEPLOYING CHATBOTS IN TRUSTED COMPANIONSHIP ROLES
PhD, Principal Supervisor
Other supervisors: Professor Renata Meuter - Becoming DTube: The biography of a decentralised video streaming platform
PhD, Associate Supervisor
Other supervisors: Professor Jean Burgess - Emerging digital technologies for development: International digital inclusion agendas
PhD, Associate Supervisor
Other supervisors: Professor Michael Dezuanni - Decoding the Political Ideology of Internet Meme Subcultures Using Pragmasemiotic Methods
PhD, Associate Supervisor
Other supervisors: Professor Jean Burgess, Dr Ariadna Matamoros Fernandez