This document discusses identity in physical, cyber, and future contexts. It defines identity as having three layers: a personal identity, shared identities through groups and interests, and abstracted identities through demographics. Physically, identity includes real-world attributes, while cyber identity involves online profiles and behavior. The document analyzes how users' identities in online platforms converge towards social norms over time before transitioning away. It suggests future identity will involve a blended lens between the physical and cyber layers, with development becoming co-dependent across both and all boundaries being conventions to transcend.

1. IDENTITY: PHYSICAL,
CYBER, FUTURE
MATTHEW ROWE
LANCASTER UNIVERSITY, UK
WWW.LANCASTER.AC.UK/STAFF/ROWEM
@MROWEBOT
Dagstuhl Seminar: Physical-Cyber-Social Computing –
September/October 2013

2. Identity: Physical, Cyber, Future
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So ‘identity’; what do we mean?

3. Identity: Physical, Cyber, Future
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So ‘identity’: what do we mean?

4. Identity: Physical, Cyber, Future
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My
Identity
Shared Identity
Abstracted Identity
Persistent information
Never changes
More detailed
Information
More prone
to change
Groups and demographics
Interests and tastes

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My
Identity
Shared Identity
Abstracted Identity
Physical
My ‘real world’ name
My parents and siblings
Where I live
My friends
My neighbours
My interests & hobbies
Society memberships

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My
Identity
Shared Identity
Abstracted Identity
Cyber
My username/handle
Where I say I live
My connections
My stated interests
My behaviour

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My
Identity
Shared Identity
Abstracted Identity
Cyber
Intentional
(ego)
Existential
My username/handle
Where I say I live
My connections
My stated interests
My behaviour

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Development =
conflicts
Development
happens through
stages

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10. How do users’ identities develop within cyber systems over time?
Identity: Physical, Cyber, Future
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by computing the cross-entropy of one probability distri-
bution with respect to another distribution from an lifecycle
period, and then selecting the distribution that minimises
cross-entropy. Assuming we have a probability distribution
(P) formed from a given lifecycle period ([t, t0
]), and a
probability distribution (Q) from an earlier lifecycle period,
then we define the cross-entropy between the distributions
as follows:
H(P, Q) =
X
x
p(x) log q(x) (5)
In the same vein as the earlier entropy analysis, we
derived the period cross-entropy for each platform’s users
throughout their lifecycles and then derived the mean cross-
entropy for the 20 lifecycle periods. Figure 3 presents the
cross-entropies derived for the different platforms and user
properties. We observe that for each distribution and each
platform cross-entropies reduce throughout users’ lifecycles,
suggesting that users do not tend to exhibit behaviour that
has not been seen previously. For instance, for the in-degree
see a consisten
forming user
set of posts
the probabil
instance, for
frequencies
discrete prob
(P[t,t0]), and
time interval
between the
As before
each platform
the mean co
Figure 4 pre
degree, out-d
periods. We
entropy of u
Identity properties @ time t
Identity properties @ time t of the social system (norms)
Dissimilarity between the properties

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Out-degree distribution of users:
Greater
dissimilarity
Time in the system
Converge towards social norms,
before transitioning away
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2.03.04.05.0
Lifecycle Stages
DistributionCrossEntropy
0 0.2 0.4 0.6 0.8 1

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Lexical distribution of users:
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6.06.57.07.58.08.5
Lifecycle Stages
DistributionCrossEntropy
0 0.2 0.4 0.6 0.8 1

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What is happening here?!1!

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6.06.57.07.58.08.5
Lifecycle Stages
DistributionCrossEntropy
0 0.2 0.4 0.6 0.8 1
Identity: Physical, Cyber, Future
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Identity achievement: divergence from normsForeclosure: convergence on social norms
Changing with Time: Modelling and Detecting User Lifecycle Periods in Online Community
Platforms. M Rowe. To appear in the proceedings of the International Conference on Social
Informatics. Kyoto, Japan. (2013)
Mining User Lifecycles from Online Community Platforms and their Application to Churn
Prediction. M Rowe. To appear in the proceedings of the International Conference on Data
Mining. Dallas, US. (2013)

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My
Identity
Shared Identity
Abstracted Identity
Cyber Physical
Future = lens blend
• Development being co-dependent between physical and cyber layers
• Transcendent identity (theories, recommendations, development)
“All boundaries are conventions, waiting to be transcended”

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¨ Informing social theory from cyber layer’s
interpretation, and vice versa
¨ Behaviour diffusion through developmental stages
¨ Pre-empting physical decisions through
understanding of the cyber lens
¨ Redefinition of cross-lens social norms

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Questions?