Dr Alexia Maddox, Lecturer in Communications, School of Communications and Creative Arts, Deakin University. Email: a.maddox@deakin.edu.au 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. https://soundcloud.com/user-475470975/detecting-disruptive-events-within-digital-communities

1. Dr Alexia Maddox
detecting disruption
Visualizing data from digital
communities surrounding
cryptocurrencies and the dark
web
Twitter: @alexiamadd

2. Overview
❖ Research agenda
❖ Visualising social form
❖ Characterising digital communities
❖ Social surfaces
❖ Data alignments for visualisation
❖ Socio-technical disruption
❖ Case study 1: cryptocurrency community(ies)
❖ Case study 2: Dark web community(ies).

3. Research context
❖ Social Scientist specialising in the study of digital communities,
digital social frontiers, and digital research methods including
❖ the study of collective behaviours online
❖ social media use
❖ digital cultures
❖ research methods to observe, monitor and engage online cohorts.
❖ Themes of social change, social cohesion, social activism and
social inclusion.

4. Research vision
❖ Generate a data recognition practice (AI/machine learning)
❖ model social intelligence in 3D immersive environment.
❖ search for signatures of social disruption within digital
trace data.
❖ Interactive and predictive analysis (historical and real
time).
❖ Identify non-human actors within social datasets that
influence social sentiment.

5. Research agenda
❖ Investigating available data, techniques and community
processes suitable for modelling and visualisation.
❖ Building collaborations through an interdisciplinary
network of researchers across the social sciences,
humanities and computational sciences (but not limited
to!).
❖ Developing an interactive and immersive platform for
researchers and research stakeholders to model social
processes.

6. Visualising social form

7. Modelling social form
Maddox, circa 2014 (vintage graphics!)

8. Maddox, A 2016, Research
Methods and Global Online
Communities: A Case Study,
Routledge, London, UK.
Figure: Methods for collecting data on digital community

9. Figure: Conceptualizing the link between egocentric data imprints to digital
community
Modelling individual
practices
Maddox, A 2017, 'Beyond digital dualism: Modeling digital community', in T Cottom, J
Daniels & K Gregory (eds), Digital Sociologies, Policy Press, Bristol, UK, pp. 9-26.

10. http://www.infinitelooper.com/?v=L-cxg8mF_Lw&p=n#/519;590
Serendipity & Social Surfaces
Maddox, circa 2014 (yes, Chromatophores!)
Deravi, LF, Magyar, AP, Sheehy, SP, Bell, GR, Mäthger, LM, Senft, SL,
Wardill, TJ, Lane, WS, Kuzirian, AM & Hanlon, RT 2014, 'The structure–
function relationships of a natural nanoscale photonic device in cuttlefish
chromatophores', Journal of The Royal Society Interface, vol. 11, no. 93, p.
20130942. http://rsif.royalsocietypublishing.org/content/11/93/20130942

11. Socio-technical disruption

12. Socio-technical disruption
❖ Hypotheses directing investigation:
❖ Digital communities generate and appropriate emerging technologies
to create alternative possibilities.
❖ Socio-technical disruption is manifested through digital communities.
❖ Socio-technical disruption may be identifiable through digital
signatures.
❖ Forms of identifiable disruption may be ambivalent, malicious or
resistance/refusal acts against structural inequalities.
❖ Within a community this can be characterised through both internal
events and externalised activities.

13. Case study 1: Cryptocurrencies
❖ To study public discourse surrounding cryptocurrencies via social
media analysis.
❖ Cryptocurrencies are:
❖ Digital payments systems
❖ based upon decentralised peer-to-peer exchange practices
❖ Use of encryption technologies for user privacy and anonymity.
❖ Contentious developments widely discussed within social
media surrounding cryptocurrencies over the last five years
(2012-2017).

14. Data gathered through TrISMA archive and processed through Tableau (unpublished)
Figure: Cryptocurrency discussion in the Australian Twittersphere 2012 to early 2017

15. Case study 1: Cryptocurrencies
❖ Community profile
❖ Origins within the Cyber-libertarians of the 1990s (Cypherpunks email
list formed in 1992).
❖ Value field includes: privacy, anonymity, personal sovereignty &
autonomy, freedom (of information and by contractual relationships),
disruption of state, decentralisation, peer-to-peer socio-technical
architectures, code-as-law.
❖ Goldbugs, hippies, cyberlibertarians and so on … (Maurer 2013).
❖ Cypherpunks and Crypto-anarchists (Swartz 2018).
❖ Broader base includes fintech enthusiasts and speculators, start ups and
entrepreneurs, privacy advocates.
Maddox, A, Singh, S, Horst, H & Adamson, G 2016, 'An ethnography of Bitcoin: Towards a future research
agenda', Australian Journal of Telecommunications and the Digital Economy, vol. 4, no. 1, pp. 65-78.

16. Case study 1: Cryptocurrencies
❖ External disruption
❖ Community agenda towards the disruption of
centralised banking system
❖ Frictionless transfers across national borders (ie
stateless transfer).
❖ Blockchain developments (cf. Allen 2018, Zhao
2016)

17. Case study 1: Cryptocurrencies
❖ Internal disruption
❖ There have been several contentious events within
the community (ie forking in the blockchain, hacks
and scams).
❖ These are disputes surrounding what the
technologies can or should do linked to disputes
between values.

18. Case study 1: Cryptocurrencies
❖ Trends & tensions over 2012-2017
❖ Incorporation of these technologies within banks
❖ Scams and hacks through exchanges and ICOs
❖ Centralising forces & middle men
❖ Investment/speculation bubble
❖ Digital metallism vs infrastructural mutualism
(Swartz 2018).

19. Case study 2: Cyberlibertarians
❖ To study cyber-libertarian discourse within the
contentious environments of the dark web.
❖ To investigate the relationship between passive data
monitoring (big data analysis) and data gathered
through active engagement (small data analysis)
❖ Consider how this combination of data can inform
and disrupt assumptions within data visualisation
approaches.

20. Case study 2: Cyberlibertarians
❖ Dark web environments
❖ Overlapping values towards the sovereign self, personal privacy
and anonymity.
❖ Nodal governance of online spaces
❖ Expression of radical values (information freedom, radical
transparency, radical anti-statism).
❖ Cyber-libertarianism 2.0: anarcho-capitalism of the sharing
economy & DIY prosumers freed from external constraint
(Dahlberg 2010).
❖ Technology-enabled solutions to social problems
❖ Self-organising practices of resistance (cf. Fuchs, Coleman)

21. Case study 2: Cyberlibertarians
❖ Cryptomarkets
❖ Choice-driven drug
purchasing online
❖ Constructive activism
❖ Contentious visibility
❖ ‘Selfcare’ vs ‘Healthcare’
Maddox, A, Barratt, MJ, Allen, M & Lenton, S 2015, 'Constructive activism in the dark web: cryptomarkets and illicit drugs in the
digital ‘demimonde’', Information, Communication & Society, pp. 1-16.
Barratt, MJ, Lenton, S, Maddox, A & Allen, M 2016, '‘What if you live on top of a bakery and you like cakes?’—Drug use and harm
trajectories before, during and after the emergence of Silk Road', International Journal of Drug Policy, vol. 35, pp. 50-7.
Barratt, MJ & Maddox, A 2016, 'Active engagement with stigmatised communities through digital ethnography', Qualitative Research,
vol. 16, no. 6, pp. 701-19.
https://anthrodendum.org/2018/01/22/a-digital-bermuda-triangle-the-perils-of-doing-ethnography-on-darknet-drug-markets/

22. Case study 2: Cyberlibertarians
❖ External disruption
❖ Constructive activism: building a new world in the
shell of the old.
❖ Online privacy and digital rights movement
❖ Internal disruption
❖ Hacks and Scams, DDOS attacks, Doxxing , site
seizure by law enforcement, digital diasporas in
digital spaces

23. Methodological challenges abound
❖ Defining and locating the community to study.
❖ Gaining consent and engagement and addressing the many ethical
quandaries.
❖ Decisions on which methods and data collection tools.
❖ Identification of appropriate data sources
❖ Data capture: data on the dark web tends towards the ephemeral.
❖ How to render social intelligence into 3D formats (multi-factor
visualisation).
❖ How to incorporate machine learning and AI approaches to process
social intelligence (archival and real time information).

24. Next steps
❖ Keep plugging away at case study 1
❖ Identify appropriate subject of study for case study 2
❖ Identify and map available data sources
❖ Investigate 3D visualisation tools and Machine learning/AI tools.
❖ Determine funding sources to support the development of this project
❖ Identify and engage collaborators and build a research network/ engage
and interdisciplinary field
❖ Publish, publish, publish
❖ Stay employed long enough to develop critical mass around this project!