Deeply mining user online behaviour with social event influence (2018–2021)

Abstract:
This research aims to investigate the effect of external stimulation, such as big news stories, on user online behaviour. Although social event detection has been actively researched in recent years, there is no systematic study of how social events can influence user behaviour and thus this proposal represents a new dimension in online behaviour analytics. The system prototype to result from this Fellowship will include a novel event database indexing structure to enable large-scale event detection and monitoring over continuous social media streams, and an innovative genre of features for effective behaviour modelling. Outcomes are expected to contribute to the research priority area - lifting productivity and economic growth.
Grant type:
UQ Development Fellowships
Researchers:
  • Associate Professor
    School of Information Technology and Electrical Engineering
    Faculty of Engineering, Architecture and Information Technology
Funded by:
University of Queensland