antonio a. casilli - networks, complexity, and privacy

Institut Mines-Télécom

Networks, complexity, and privacy

Antonio A. Casilli

(Telecom ParisTech SES)

Institut Mines-Télécom04/07/20232

Social networks

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If I say «social network»

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Social network: a way of describing human groups as a set of social actors (nodes) and relationships existing among them (ties)

Human groups as networks

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Central Members

Bridges

Group Members

Isolate

Peripherals

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Is computer-mediated interaction changing the overall structure of human networks? Comparing computer-mediated and face-to-face

relationships: which networks are larger? Further refinements: are personal networks mainly

composed of "strong" or "weak" ties? Are there more weak ties in online personal networks?

Are personal networks densely knitted, or sparse? Are online personal networks sparser?

Computer-mediated interactions

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1992 Robin Dunbar

148

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290

2000 Peter Killworth

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610

2010 Matthew Salganik

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2012

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1969: six degrees of separation

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2012: four degrees of separation

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Institut Mines-Télécom

Two possible explanations

Higher transitivity of online networks

Presence of big hubs

25 Télécom ParisTech


04/07/2023


Different types of online «social capital»

Bonding : homogenous groups and cohesion Bridging : information circulating among heterogenous groups

Bonding

Bridging

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From a “little boxes” society

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…to “networked individualism”?

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Institut Mines-Télécom04/07/202329 Télécom ParisTech



“Glocal” networks

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Experiment: create two accounts The fomer (actual profile) discloses

more personal details, the latter (control profile) discloses less

Invite 100 users to friend them (50 each)

Friends provide feedback on how to enrich profiles (Comments, Messages, Likes, Shares)

Compare two accounts over 50 days

A social media experiment

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Observation notes:

– « Jusqu’à aujourd’hui, les retours sur les deux profils sont assez négatifs. Les connaissances de sexe féminin surtout ne se gênent pas pour exprimer leur aversion. Une amie définit le profil 1 comme ‘effrayant’, une autre qualifie la photo du profil 2 de ‘monstrueuse’ ».

–« Indication : utilisateur du profil 1 apprécie la cuisine japonaise et écoute de la musique punk. Il lit des bandes dessinées et des poètes de la beat generation ».

–« Profil 1 constamment ouvert dans mon navigateur. En automatique des petites fenêtres contenant des suggestions ou des ‘morceaux choisis’ par ses amis. ‘L’utilisatrice X est fan de l’artiste peintre Tel’ ; ‘L’utilisateur Y a aimé le dernier livre de l’écrivain Telautre’ ».


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1. Two Facebook profiles initial state


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2. Profile 1 discloses personal preferences


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3. Profile 1 discloses bio


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4. Profile 1 uploads a photo album


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Compare social graphs

Disclosing profile has a larger, more varied network

Better management of social capital: balance bw bonding (social cohesion) and bridging (social connectivity)


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Bridging

Bonding


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Studying complexity

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Complexity and social science

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Chaos, social dynamics, emergent behaviours


Complexity and social science

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Social systems, self-organization, autopoiesis, complex adaptive systems


Agent-based modelling

Agent-based computer simulations

Generate socially consistent scenarios on a computer;

Analyse the resulting scenario outcomes to:

Identify sufficient conditions under which different outcomes emerge;

Assess their sensitivity to parameter changes.

An aid to perform a thought experiment.

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The 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.

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KISS (Keep It Simple and Stupid)

Schelling’s segregation model (1973)

How tolerant individuals have to be in order to avoid collective segregation (the creation of ghettoes) in a given social space?

Some surprising results…

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‘‘Pure’’ models ‘‘Empirical’’ models

. Built by abstraction from a target system (a social phenomenon or context).

. Mainly regarded as tools for generating, expressing and testing theories.

. Not always realistically representing choices and behaviors at the micro level.

. Enable in-depth reflection on the possible unintended social consequences of purposeful individual actions.

. Open to estimation and validation via qualitative and quantitative data.

. Quantitative data can be used to assess the probability that a certain event takes place within a given population of agents (either predictively or retrodictively).

. Use of qualitative data to inform simulation rules and parameters is also attested since the late 1990s (structural validation).



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Privacy

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Institut Mines-Télécom04/07/2023 Télécom ParisTech51

The privacy challenge in social media

Periodic privacy incidents on FB

Mark Zuckerberg: ”Public is the new social norm”

Are we approaching the “End of Privacy” as we know it?

Alleged tendency to "renounce privacy" for an open, connected existence (publicness)?

The end of privacy online?

Institut Mines-Télécom04/07/202354 Télécom ParisTech

Date Privacy-related incident Users’ reaction

05/09/2006 Introduction of News Feed (content and user updates aggregator).

Users’ uproar over the default opt-in policy. Creation of the advocacy group “Students against Facebook News Feed” to protest the new feature. The group attracts almost 300,000 members, leading to apologies by Mark Zuckerberg, Facebook’s funder and CEO.

26/09/2006 Facebook reinforces privacy options for users (to limit searchability and tie formation) to anticipate the gradual opening of its membership to any US and Canada college students with a valid email address and over the age of 13.

06/11/2007 Introduction of Beacon (advertising system aggregating purchase data over several platforms, most prominently Amazon).

Prominent political activist group MoveOn.org creates an online petition against Beacon. Their Facebook group reaches 50,000 members, which leads Mr Zuckerberg to issue an official apology. Beacon ultimately shut down in September 2009.

09/12/2009 Facebook changes its privacy settings, making sharing with everyone compulsory: legal names, profile pictures, and gender are now public by default.

An alliance of privacy organisations files a complaint with America’s Federal Trade Commission (FTC).

21/04/2010 Facebook introduces the Like button social plugin for external websites. Users can now log in, like and share contents (“frictionless sharing”) on other services through their Facebook account.

Prompted by their constituents, a group of American senators asks the FTC to establish privacy guidelines for Facebook. Privacy groups file a formal complaint to the FTC against Facebook’s “unfair and deceptive trade practice of sharing user information with the public and with third-party application developers”. At the end of May 2010, Mr Zuckerberg announces new and simplified privacy settings.

14/01/2011 Facebook makes users’ addresses and phone numbers available to external websites.

After negative feedback from users, Facebook disables the feature. At the end of the month, the fan page of Mr Zuckerberg is hacked and compromised. The following day, Facebook starts implementing https secure pages.

08/2011 Following a series of complaints filed by Austrian student association Europe v. Facebook. org, it emerges that Facebook fails to comply with the rule of allowing its users to download their own personal data: it provides only 39 over 84 personal data categories.

Negative media attention and creation of several campaigns requiring Facebook to give users full access to their data.

05/2012 Facebook proposes a new and more complex privacy policy while asking for generic “users’ feedback”.

40,000 user comments force vote on proposed alternatives to privacy policies.

20/06/2012 Facebook announces acquisition of facial recognition technology company Face.com (creates database of users’ biometric information through photo-tagging).

Privacy advocacy groups file complaint to the FTC recommending suspension of facial recognition technology and protesting creation of biometric profiles of users without their explicit consent.


To find an answer to this question let’s try and build an agent-based model that represent the possible equilibriums for a system of agents disclosing personal informations online

Phase 1: empirical observation

Phase 2: modelling

1

2

Modelling privacy


Remember our experiment on disclosure

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?

Modelling privacy


Problematizing privacy In fact, online interactions

complexify the very notion of privacy

Traditional notion based on metaphor of concentric circles of intimacy

Mono-directional notion: a core of sensitive data to be protected.

This notion no longer seems adapted to interactions in a networked society.

Modelling privacy


Privacy as a multi-directional, dynamic process

Online privacy better described through multi-directional negotiation

Individuals send signals to, and receive feedback from, their social environment.

Self-disclosure accompanies adaptation to signals from the (social) environment over time.

Modelling privacy


We need to design 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?

Modelling privacy


Behavioral rules:• Tie formation allowing for both

bonding and bridging social capital;• Binary on/off visibility settings;• Homophilous choice of network

contacts.

Parameters:• Tendency to value bonding /

bridging social capital;• Openness to cultural diversity.

Indicators:• Mean privacy level;• Number and size of components.

Our simulation model


Resulting system configurations


(1) Echo-chambers (2) Large components (3) Generalized connectedness.


How parameter values affect results


Treemap: varying modes of valuing bonding/bridging ties and levels of cultural openness. Size of rectangles is proportional to size of largest network component, colour represents differences in number of components.


Effects on social division• When bonding prevails, echo-

chambers always emerge regardless of the cultural openness of agents;

• When bridging prevails, the degree of cultural openness determines whether the result is one or few large components.

Effects on privacy choices• When bonding prevails, average

privacy changes little regardless of the cultural openness of agents;

• When bridging prevails, high cultural openness prompts increased privacy protection.


Evolution of mean privacy over time, with high bridging social capital and high cultural openness.


Network structure matters• Relative value of

bonding/bridging ties affects final outcomes;

• Homophily need not be socially divisive;

Important to focus on motivations on people to form social capital online;

Networking service architecture likely to play a key role.

Results

Evolution of mean privacy over time, with high bridging social capital and high cultural openness.


No “End of Privacy” in sight

Social media usage is not bound to destroy privacy

It is when connectedness is at its highest that privacy re-surfaces;

It becomes important to consider users’ attitudes in discussions of providers’ privacy policies.

Results

Privacy cycles in the presence of service provider interventions to unlock privacy setting by default


Thank you!

Email : [email protected] Blog : http://www.bodyspacesociety.eu Twitter : @bodyspacesoc

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antonio a. casilli - networks, complexity, and privacy

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