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Dr Alexia Maddox, Lecturer in Communications, School of Communications and Creative Arts, Deakin University.
From a community studies perspective the adaptation of digital communities to dynamic environments has meant that they are more difficult to detect and characterise. However, I argue that the built environment of a digital community can be understood through its digital and material construction articulated within social practices of engagement (ie where people are actively connecting with each other). In my previous work characterising the community of people with reptile interests, I offered a conceptual model of social ecology. This model was built with the key agenda to support the animation of social form through dimensional understandings of socio-technical connections from physical place to code. Here I offered connected research that illustrated ways to identify the built environment, the social layer and the mediating culture of a community. This model aimed to support the production of layered data that created social surfaces where there are densities of interaction. Moving to my present research into the community surrounding cryptocurrencies, I am progressing through three case studies that seek to provide data surfaces that can model community processes, particularly those that are disruptive. In this paper, I discuss these three case studies and their progressive illustrations of both internal and external disruption within community structures. The first study broaches a social media analysis of public discourse surrounding cryptocurrencies. It will focus on identifying and characterising contentious engagements and community disputes over the last five years. The second case study will move to working with cyber-libertarian discourse within the contentious environments of the dark web. The method for this study is yet to be determined and is likely to combine digital trace data analysis with community engagement. This study will seek to generate big data-small data relationships that provide both the digital imprint and lived experience of internal and external disruption within a radical community context. The final case study will work to identify ways to visualize the information collected and curated in case study one and two into 3D data visualization formats. The aim here will be to generate data recognition practices to search for signatures of socio-technical disruption, where disruptive events characterise tensions and tipping points for community cohesion.