The Network Connection

Yasmin Merali

yasminmerali2@gmail.com

Thoughts about

Context: the interconnected world Socio-economic systems as CAS The network signature Knowledge Management and the

“networkness” of networks

Interconnected world

Internet

connectivity information

Dynamic context

organisation

Emergence ...

Networks and the Inter-connected World

© Yasmin Merali 2013

Network dynamicsNetwork effects

Responsiveness and FitnessAdaptive &Transformational capacity

Uncertainty DiscontinuitySpeed

Network economy...

Non-equilibrium dynamics

Nonlinearity, network effects

Uncertainty

Ecologies

Yasmin Merali 2013

Agility and Intelligence

Intelligence: internal and external Dynamic contextualisation Speed and Resilience

Act fast (and recover fast from mistakes) Keep options open Maintain reconfiguration capacity (structure and components)

Exploit the networkness of networks

Complex Adaptive Systems

Open Network signature – non-linear dynamics Emergent systemic properties

CAS and the “Networkness of Networks” Nonlinearity – potential for

maintaining steady state and transformation

Requisite Variety: microdiversity, heterogeneity of Types of links Properties of the nodes Types of info and knowledge flows Degree of connectivity and density of connections

Patterns of connectivity and combinatorial potential Potential/latent/active reach/connectivity Mutually defining relationship of dynamics and structure

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KNOWLEDGE MANAGEMENT AND THE NETWORKNESS OF NETWORKS

Social networks as Information Networks

social networks viewed as information networks embodying communication and meaning

Complexity of social information networks

–Nodes– Links– Informational Content

}Dynamics HeterogeneityVariable persistenceCo-presence

Risky Business

Connectivity: the speed and spread of diffusion of information (or mis-information)

Information content: the ability of nodes to transform the message, strip or attach context

Signal or Noise?

STRUCTURE AND DYNAMICS

Examples: Network Structure and Non-linear Dynamics Matter

Internet: structure and vulnerability to attack Epidemiological models for spread of diseases Social applications:

—Imitation, flocking and herding behaviours—opinion dynamics, —influencing behaviours, —logistics (e.g. mobility patterns and urban

planning)

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Patterns of Connectivity and Control

CAS as networks of networks

Han et al (Nature, 430, 88-93 , 2004) – Date Hubs: regulators, mediators or adaptors

(selectively connected across modules)– Party Hubs: integral elements within distinct modules (densely

connected nodes within modules)

Networks of Networks

Yasmin Merali 2013

INFORMATIONAL COMPLEXITY

shift from dealing with observation s of the world to dealing with others’ representations of possible worlds…

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Information Quality Interpretation

Representation

Both are selection, abstraction and recombination exercises raising questions about the need for

—Context (-ual filtering)—Cognitive Filtering—Social Filtering

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Cognition Sensemaking and Heuristics:

—the embedded rules we have are derived from the environment

—social media present us with a different environment from that of the past

Social Strategies: Lower cognitive load, search cost etc —Rely on others’ opinions (e.g. recommendations, reviews,

likes)—Decide who we trust (whose recommendations we follow)

vs decide what we think of the “raw data”

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The Problem of Abstraction

Choosing the requisite level of abstraction

Moving between levels: loss of detail vs loss of dimensions

Moving between dimensional views?

Who controls − the level of abstraction− the dimensions to include?

A requisite dimensionality?

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Representation & Interpretation

Technical level: storing, reconciling and choosing between alternative interpretive and representational frames.

Individual level: application of appropriate interpretative frames for received representations and for creating for a diverse audience

Collective level: legitimisation and imposition of representational and interpretive frames to be used by individual agents on behalf of the collective

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... the importance of context, social and cognitive scaffolding

Big Data Looking for correlations and patterns in large volume data to

extract meaning and trends

Some Issues with attributing causality to correlations:

- Loss of context – Loss of meaning – reference problem

- Checking big data- generation of history expensive and many possible paths exist.

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shift from dealing with observation s of the world to dealing with others’ representations of possible worlds, where others may be humans or machines.

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Who controls the network?

Who controls the message?