Doctor of Philosophy (Swinburne Institute of Technology)
Daniel Angus is Associate Professor of Digital Communication in the School of Communication at Queensland University of Technology. His research focuses on the development of visual computational analysis methods for communication data, with a specific focus on conversation 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 15 years and contributes regularly to media and industry on the impact of technology on society.
Daniel received the 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 currently an Associate Investigator with the ARC Centre of Excellence for the Dynamics of Language, and a member of QUT’s world-leading Digital Media Research Centre.
Projects (Chief investigator)
- Visual analysis of communication in health care: extending Discursis software to Cantonese data sets
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 p261-267
- Angus D, Wiles J, (2018) Social semantic networks: Measuring topic management in discourse using a pyramid of conceptual recurrence metrics, Chaos: An Interdisciplinary Journal of Nonlinear Science p1-12
- Carah N, Angus D, (2018) Algorithmic brand culture: participatory labour, machine learning and branding on social media, Media, Culture and Society p178-194
- Angus D, Fitzgerald R, Atay C, Wiles J, (2016) Using visual text analytics to examine broadcast interviewing, Discourse, Context and Media p38-49
- 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 p43-47
- Angus D, Smith AE, Wiles J, (2012) Conceptual recurrence plots: Revealing patterns in human discourse, IEEE Transactions on Visualization and Computer Graphics p988-997
- Angus D, Watson B, Smith AE, Gallois C, Wiles J, (2012) Visualising conversation structure across time: Insights into effective doctor-patient consultations, PLoS One p1-12
- Byrne L, Angus D, Wiles J, (2019) Figurative frames: A critical vocabulary for images in information visualization, Information Visualization p45-67
- Angus D, Smith AE, Wiles J, (2012) Human communication as coupled time series: Quantifying multi-participant recurrence, IEEE Transactions on Audio, Speech and Language Processing p1795-1807
- Baker R, Angus D, Conway-Smith E, Baker KS, Gallois C, Smith AE, Wiles J, Chenery HJ, (2015) Visualising conversations between care home staff and residents with dementia, Ageing and Society p270-297