Overview
I specialise in computational social science, particularly the applications of network science techniques and text analysis to a wide range of communication types including both social and legacy media.
My research typically focuses on understanding how media content gains attention, often through the lenses of polarisation, campaigning efforts and external shocks. My interests often follow these themes into exploration of how competing viewpoints emerge and the effects of social structures on the wider social impact of these communications platforms. Typically, my research centres on developing and testing novel methods for understanding large, complex datasets.
Primarily, I work within the Centre for Climate Change Communications and Data Science, and therefore much of my research uses climate change discourse as a case study. I have a number of ongoing projects in this area including the use of semantic similarity to quantify the effectiveness of strategic communications, network and NLP perspectives on key actors in contextual coverage of climate change and the use of computer vision techniques to better understand the editorial choices of climate visuals.
I am also keen to foster interdisciplinary connections to expose new data sources to scalable computational analyses and raise awareness of the opportunities they can provide.
Publications
Copyright Notice: Any articles made available for download are for personal use only. Any other use requires prior permission of the author and the copyright holder.
2023
- Cann TJB, Dennes B, Coan T, O'Neill S, Williams HTP. (2023) Using Semantic Similarity and Text Embedding to Measure the Social Media Echo of Strategic Communications. [PDF]
