A year of discursive struggle over freedom of speech on Twitter: What can a mixed-methods approach tell us?

This work-in-progress paper provides an interdisciplinary approach, combining large-scale quantitative Big Data oriented approaches, with small-scale qualitative deep-reading, in order to investigate a polarising debate in the Australian socio-political environment. In 2016, there were calls by some conservative political figures in Australia to make changes to a section of the country's Racial Discrimination Act (RDA). They claimed this particular section of the Act---section 18(C)---restricted freedom of speech in the public sphere. The proposed changes created heated discussions between the proponents and opponents, which were also reflected on Twitter. Using digital methods, a corpus of approximately 500,000 tweets was analysed to identify the various discursive communities and structures in the network, investigate information flows between them, and test for the existence of echo chambers and filter bubbles. The findings show that the ideological orientation of actors mostly reflects their long-term positioning in their respective networked discourse communities, and that information is disseminated freely between antagonistic network clusters, with little to no evidence of filter bubbles.