Digital emotion regulation
Project Leader: Greg Wadley
Staff: Jorge Goncalves, Vassilis Kostakos, Wally Smith, Greg Wadley
Collaborators: Peter Koval (Melbourne School of Psychological Sciences), Mario Alvarez-Jimenez (Melbourne School of Psychological Sciences), Anna Cox (University College London), James Gross (Stanford University)
Primary Contact: Greg Wadley (email@example.com)
Keywords: data mining; emotion; mobile phones; ubiquitous computing
Disciplines: Computing and Information Systems
We want to understand and measure how people engage in digital emotion regulation (digital ER); that is, the use of digital technologies to shape emotion. This involves two streams of work:
- Track people’s emotional states and technology usage to identify instances of emotion regulation. This is a technical stream involving software development and statistical methods;
- Use ethnographic methods to understand how people engage in digital ER in natural setting. This stream involves qualitative methods.
Individual candidates may choose to participate in either or both of the streams.
We are seeking high-quality PhD candidates to work with us. Candidates should be experienced in one or more of the following areas: computer science, human-computer interaction, ubicomp, quantitative and qualitative methods.
This project will inform debates about technology use and its impact in work, education and social settings. The knowledge created will inform policy-makers, designers and end-users about appropriate use of technology.
- Brans, K., P. Koval, P. Verduyn, Y. L. Lim and P. Kuppens (2013). The regulation of negative and positive affect in daily life. Emotion 13(5): 926.
- Collins, E. and Cox, A.L. (2014). Switch on to games: Can digital games aid post-work recovery?. International Journal Of Human-Computer Studies, 72 (8-9), 654-662.
- Ferreira, D., Kostakos, V. and Dey, A. K. (2015). AWARE: Mobile context instrumentation framework. Frontiers in ICT, vol. 2, no. 6, pp. 1-9.
- Gross, J. J. (2015). Emotion regulation: Current status and future prospects. Psychological Inquiry, 26(1), 1-26.
- Newbold, J. W., J. Luton, A. L. Cox and S. J. Gould (2017). Using nature-based soundscapes to support task performance and mood. CHI Extended Abstracts.
- Sarsenbayeva, Z., D. Ferreira, N. v. Berkel, C. Luo, M. Vaisanen, V. Kostakos and J. Goncalves (2017). Vision-based happiness inference: a feasibility case-study. UbiComp, ACM.
- Wadley, G. (2016). Mood-enhancing technology. In Proceedings of the 28th Australian Conference on Computer-Human Interaction (pp. 326-332). ACM.
Photo courtesy of Hugh Han on Unsplash