Simulating online privacy Simulating online privacy Ethno-computational insights Paola Tubaro1 Antonio A. Casilli2 1 University of Greenwich, London 2 TELECOM ParisTech and EHESS, Paris Sunbelt XXXII, 18 March 2012
Simulating online privacy IntroductionThe privacy challenge in social media Periodic privacy incidents on FB; Alleged tendency to renounce privacy for an open, connected existence; Mark Zuckerberg: ”Public is the new social norm”; Are we approaching the “End of Privacy” as we know it? The notion of publicness from Jürgen Habermas. . . to Jeﬀ Jarvis.
Simulating online privacy Introduction Preliminary ethnographic evidenceFB ethnography Small data approach; Experiment: create two proﬁles; Invite 100 contacts to become friends; One of the two proﬁles discloses, the other is a control proﬁle; FB friends provide feedback on how to enrich and develop proﬁle (comments, messages, likes, shares, etc.); Compare the two proﬁles over 50 days. A.A. Casilli (2010) Les liaisons numériques. Vers une nouvelle sociabilité ? Paris, Seuil.
Simulating online privacy Introduction Preliminary ethnographic evidenceThe importance of disclosure on FB Compare social graphs of two proﬁles; Personal network of actual proﬁle continues to grow in size and displays a distinctive balance between social cohesion (bonding) and social connectedness (bridging); Disclosure is crucial: does this necessarily validate the ‘End-of-privacy’ hypothesis? A.A. Casilli (2010) Les liaisons numériques. Vers une nouvelle sociabilité ? Paris, Seuil.
Simulating online privacy Introduction Theoretical frameworkProblematizing privacy In fact, online interactions complexify the very notion of privacy; Traditional notion based on metaphor of concentric circles of intimacy; Mono-directional notion (Brandeis): a core of sensitive data to be protected. ⇒ This notion no longer seems well adapted to interactions in a networked society.
Simulating online privacy Introduction Theoretical frameworkPrivacy as a multi-directional, dynamic process Online privacy better described through multi-directional notion of privacy as regulation (Altman); Brunswik’s lens model: Individuals send signals to, and receive feedback from, the environment. ⇒ Self-disclosure accompanies adaptation to signals from the (social) environment over time.
Simulating online privacy Introduction Research questionResearch question In a social system with: Formation of personal networks through bonding and bridging; Disclosure needed to form ties; Adaptation to signals from the environment through a feedback process; What will be the ﬁnal conﬁguration of the system, in terms of degree of disclosure?
Simulating online privacy MethodsAgent-based computer simulation Generate socially consistent scenarios on a computer; Compare their outcomes; To detect and assess variables coming into play within speciﬁc social processes; To identify suﬃcient conditions for a macro phenomenon to emerge from the interaction of micro behaviours. An aid to perform a thought experiment.
Simulating online privacy MethodsThe logic of an agent-based model Generate an artiﬁcial population of agents in an environment; Endow them with basic rules of behaviour; Let them interact for a certain time and step aside; Observe outcomes at the system level at the end.
Simulating online privacy MethodsOur Simulation model Programmed and run on NetLogo (Wilensky 1999); Tie formation rules allowing for both bonding and bridging; Two embedded notions of privacy: Gradual self-disclosure and adaptation to one’s personal network, through a feedback process; Binary on/oﬀ visibility settings.
Simulating online privacy ResultsResulting system conﬁgurations Figure: Stable conﬁgurations (20,000 time steps): (1) Small subnets, (2) Supernet.
Simulating online privacy ResultsTwo solutions emerge Many small subnets where contents are locked to contexts ⇒ “Elective communities” scenario. Supernet where all contents are shared by all individuals, regardless of context ⇒ Is this the “End-of-Privacy” scenario?
Simulating online privacy ResultsEﬀects of varying parameters Figure: Number and size of nets, varying with connectedness and openness to diversity.
Simulating online privacy ResultsEvolution of privacy on/oﬀ settings Figure: Average privacy settings, varying with connectedness and openness to diversity over time. It is when individuals grow more and more connected, and share more and more contents, that privacy becomes relevant again.
Simulating online privacy ResultsFor further reﬂection The supposed “End of Privacy” scenario is in fact more complex than expected; Tendency to greater openness is not linear and may give rise to counter-tendencies; Possibility of cyclical patterns: FB zeroes out privacy settings, users retune them. Bakshy E., I. Rosenn, C. Marlow, L. Adamic (2012) The Role of Social Networks in Information Diﬀusion, http://arxiv.org/abs/1201.4145.
Simulating online privacy Results Acknowledgements We acknowledge Fondation CIGREF (ISD Programme 2011) for support. Paola Tubaro, email@example.com Antonio A. Casilli, firstname.lastname@example.org