Discursis is communication analytics technology that allows a user to analyse text based communication data, in the form of conversations, web forums and training scenarios. 

It uses natural language processing algorithms to automatically process transcribed text to highlight participant interactions around specific topics and over the time-course of the conversation. 

Discursis can assist practitioners in understanding the structure, information content, and inter-speaker relationships that are present within input data. Discursis also provides quantitative measures of key metrics, such as topic introduction; topic consistency; and topic novelty. 


  • Baker, R., Angus, D., Smith-Conway, E. R., Baker, K. S., Gallois, C., Smith, A., ... & Chenery, H. J. (2015). Visualising conversations between care home staff and residents with dementia. Ageing and Society, 35(2), 270. Read Abstract 
  • Byrne, L., Angus, D., & Wiles, J. (2015). Acquired codes of meaning in data visualization and infographics: Beyond perceptual primitives. IEEE transactions on visualization and computer graphics, 22(1), 509-518. View PDF 
  • 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, 16(3), 261-267. View PDF 
  • 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), e38014. Read Article 
  • Angus, D., Smith, A. E., & 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. View PDF 
  • Angus, D., Smith, A., & Wiles, J. (2011). Conceptual recurrence plots: Revealing patterns in human discourse. IEEE transactions on Visualization and Computer Graphics, 18(6), 988-997. View PDF 

Get in touch

For more information about this project, please get in touch:

Professor Janet Wiles 
e: j.wiles@uq.edu.au 

Project members

Professor Janet Wiles

School of Electrical Engineering and Computer Science