Coevolution of Knowledge Networks and 21 st Century Organizing€¦ · National Center for Supercomputing Applications University of Illinois at Urbana -Champaign [email protected] Coevolution

1

Noshir Contractor

Professor, Departments of Speech Communication & PsychologyProfessor, Departments of Speech Communication & Psychology

Director, Age of Networks Initiative, Center for Advanced StudyDirector, Age of Networks Initiative, Center for Advanced Study

Director, Science of Networks in Communities Director, Science of Networks in Communities --

National Center for Supercomputing ApplicationsNational Center for Supercomputing Applications

University of Illinois at UrbanaUniversity of Illinois at Urbana--ChampaignChampaign

[email protected]@uiuc.edu

Coevolution of Knowledge Networks and

21st Century Organizing

1. Turn on power & set MODE with MODE button. You can

confirm the MODE you chose as the red indicator blinks.

2. Lamp blinks when (someone with) a Lovegety for the opposite

sex set under the same MODE as yours comes near.

3. FIND lamp blinks when (someone with) a Lovegety for the

opposite sex set under different mode from yours comes near.

May try the other MODES to “GET” tuned with (him/her) if you

like.

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Social “Petworking” – Reported in Wired, April 11, 2005

Aphorisms about Networks

�� Social NetworksSocial Networks: :

� Its not what you know, its who you know.

� Cognitive Social Networks:

� Its not who you know, its who they think you know.

� Knowledge Networks:

� Its not who you know, its what they think you know.

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Source: Newsweek, December 2000

Cognitive Knowledge Networks

WHY DO WE CREATE,

MAINTAIN, DISSOLVE, AND

RECONSTITUTE OUR COMMUNICATION AND

KNOWLEDGE NETWORKS?

4

Monge, P. R. & Contractor, N. S. (2003).

Theories of Communication Networks. New

York: Oxford University Press.

Why do actors create, maintain,

dissolve, and reconstitute network links?

�� Theories of selfTheories of self--interestinterest

�� Theories of social and Theories of social and resource exchangeresource exchange

�� Theories of mutual Theories of mutual interest and collective interest and collective actionaction

�� Theories of contagionTheories of contagion

�� Theories of balanceTheories of balance

�� Theories of homophilyTheories of homophily

�� Theories of proximityTheories of proximity

�� Theories of coTheories of co--evolutionevolution

Sources:

Monge, P. R. & Contractor, N. S. (2003). Theories of Communication Networks. New York: Oxford

University Press.

Contractor, N. S., Wasserman, S. & Faust, K. (in press). Testing multi-theoretical multilevel hypotheses about organizational networks: An analytic framework and empirical example. Academy of Management Review.

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Exploring Exploiting Mobilizing Bonding Swarming

Theories of Self-Interest + --

Theories of Collective Action + + +

Theories of Cognition + + +

Theories of Balance -- + +

Theories of Exchange + +

Theories of Contagion + +

Theories of Homophily -- +

Theories of Proximity -- + +

A contextual “meta-theory” of

social drivers for creating and sustaining

communities

Core ResearchSocial Drivers for

Creating & Sustaining

Communities

Business Applications

PackEdge Community of

Practice (P&G)

Vodafone-Ericsson “Club”

for virtual supply chain

management (Vodafone)

Societal Justice Applications

Cultural & Networks Assets

In Immigrant Communities

(Rockefeller Program on

Culture & Creativity)

Economic Resilience NGO

Community

(Rockefeller Program on Working

Communities)

Entertainment Applications

World of Warcraft (NSF)

Everquest (NSF, Sony Online Entertainment)

Science Applications

CLEANER: Collaborative Large

Engineering & Analysis Network for

Environmental Research (NSF)

CP2R: Collaboration for Preparedness,

Response & Recovery (NSF)

TSEEN: Tobacco Surveillance

Evaluation & Epidemiology Network (NSF, NIH, CDC)

Projects Investigating Social Drivers for Communities

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Exploring Exploiting Mobilizing Bonding Swarming

Emergency Response

Community + + +

WoW Gaming Community + + +

Mexican Immigrant

Community + +

PackEdge Communities of

Practice + + +


Community + +

Tobacco Surveillance,

Evaluation & Epidemiology

Community

+ +

Environmental Engineering

Community + + +

Contextualizing Goals of Communities

Challenges of leveraging these networks … until now

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Daniel E. Atkins, Chair,

University of Michigan Kelvin K. Droegemeier,

University of Oklahoma Stuart I. Feldman, IBM

Hector Garcia-Molina, Stanford University

Michael L. Klein, University of Pennsylvania

David G. Messerschmitt, University of California at

Berkeley Paul Messina, California Institute

of Technology Jeremiah P. Ostriker, Princeton

University

Margaret H. Wright,New York University

The Atkins ReportThe Atkins Report

http://www.communitytechnology.org/nsf_ci_report/

Report of the

National Science Foundation

Advisory Panel on

Cyberinfrastructure

Revolutionizing

Science and

Engineering through

Cyberinfrastructure:

Enter: Cyberinfrastructure & Web 2.0

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From Mosaic to Cyberinfrastructure�� MosaicMosaic

�� By early 1990s, the internet By early 1990s, the internet

had a wealth of resources, but had a wealth of resources, but

they were inaccessible to most they were inaccessible to most

peoplepeople

�� MosaicMosaic facilitated the facilitated the accessaccess

of the Internet by of the Internet by allall

�� CyberinfrastructureCyberinfrastructure

�� Cyberinfrastructure Cyberinfrastructure will will

facilitate the facilitate the seamless and seamless and

interconnected useinterconnected use of all the of all the

digital resources on the digital resources on the

Internet (datasets, documents, Internet (datasets, documents,

sensors, analytics, computing, sensors, analytics, computing,

and communication)and communication)

For more information on NCSA’s history, see: http://www.ncsa.uiuc.edu/20years/

Multidimensional CoP Networks

Multiple Types of Nodes and Multiple Types of Relationships

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Communities



Practice (P&G)










Community


Communities)













CLEANER Community: A multidimensional network

NCSA

David

Streamflow

Analyst

Mary

CHATS WITH

USES

Hydrologic

Information System

Status Report

C-U County Hydrologic

Dataset

AFFILIATED WITH

watersheds

EXPERT IN

River Monitoring Systems

Contains as

Keyword

HUDSON

RIVER Hydro

DATA

DOWNLOADS

AUTHOR OF

Searches for Keyword Annie

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Its all about “Relational Metadata”

�� Technologies that “Technologies that “capturecapture” communities’ relational meta” communities’ relational meta--data data ((PingbackPingback and and trackbacktrackback in in interbloginterblog networks, networks, blogrollsblogrolls, data , data provenance)provenance)

�� Technologies to “Technologies to “tagtag” communities’ relational metadata (from Dublin ” communities’ relational metadata (from Dublin Core taxonomies to Core taxonomies to folksonomiesfolksonomies (‘wisdom of crowds’) like (‘wisdom of crowds’) like

�� Tagging pictures (Tagging pictures (FlickrFlickr))

�� Social Social bookmarkingbookmarking ((del.icio.usdel.icio.us, , LookupThisLookupThis, , BlinkListBlinkList))

�� Social citations (Social citations (CiteULike.orgCiteULike.org))

�� Social libraries (Social libraries (discogs.comdiscogs.com, , LibraryThing.comLibraryThing.com))

�� Social shopping (Social shopping (SwagRollSwagRoll, , KaboodleKaboodle, , thethingsiwant.comthethingsiwant.com))

�� Social networks (FOAF, XFN, MySpace, Facebook)Social networks (FOAF, XFN, MySpace, Facebook)

�� Technologies to “Technologies to “manifestmanifest” communities’ relational metadata ” communities’ relational metadata ((TagcloudsTagclouds, Recommender systems, Rating/Reputation systems, , Recommender systems, Rating/Reputation systems, ISI’sISI’sHistCiteHistCite, Network Visualization systems), Network Visualization systems)

3D Strategy for

Enhancing CoP Networks�� DDiscovery: Effectively and efficiently foster network links from iscovery: Effectively and efficiently foster network links from people people

to other people, knowledge, and artifacts (data sets/streams, anto other people, knowledge, and artifacts (data sets/streams, analytic alytic tools, visualization tools, documents, etc.). tools, visualization tools, documents, etc.). “If only we knew what we “If only we knew what we knew.”knew.”

�� DDiagnosis: Assess the “health” of iagnosis: Assess the “health” of CoP’sCoP’s internal and external networks internal and external networks -- in terms of scanning, absorptive capacity, diffusion, robustnesin terms of scanning, absorptive capacity, diffusion, robustness, and s, and vulnerability to external environmentvulnerability to external environment

�� DDesign or reesign or re--wire networks using social and organizational incentives wire networks using social and organizational incentives (based on social network research) and network referral systems (based on social network research) and network referral systems to to enhance evolving and mature communities.enhance evolving and mature communities.

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Discovery Challenges

��Who knows who?Who knows who?

��Who knows what?Who knows what?

��Who know who knows who?Who know who knows who?

��Who knows who knows what?Who knows who knows what?

Goal of Discovery –“IKNOW”

http://iknow.spcomm.uiuc.eduUse courtesy logins and passwords provided on the website

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Cybercommunity Resources

DocumentsCollaboration

Tools

Data

sharing

Analysis

Tools CI-KNOW

Portlet

David C. writes

a message on a

CLEANER

forum about

hydrological monitoring

systems.

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DocumentsCollaboration

Tools

Data

sharing

Analysis

Tools

Cybercommunity Resources

CI-KNOW

Portlet

CI-KNOW

Portlet

Recommending

People

David C.

retrieves

hydrological

datasets on C-U

County rivers

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CI-KNOW

Portlets

Why Diagnose the Network?

�� Naturally occurring networks are not always Naturally occurring networks are not always

efficient or fully functionalefficient or fully functional

�Gaps, isolates, lack or difficulty of connectivity

�� Network measures can be used to diagnose Network measures can be used to diagnose

network’s vital statisticsnetwork’s vital statistics

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Communities



Practice (P&G)










Community


Communities)













Tobacco Surveillance, Epidemiology,

and Evaluation Network (TSEEN)

�� National Cancer Institute National Cancer Institute

�� Center for Disease Control’s National Center for Center for Disease Control’s National Center for Health Statistics (NCHS), Health Statistics (NCHS),

�� Center for Disease Control’s Office of Smoking Center for Disease Control’s Office of Smoking and Health (OSH), and Health (OSH),

�� Agency for Healthcare Research and Quality Agency for Healthcare Research and Quality (AHRQ),(AHRQ),

�� National Library of Medicine (NLM) and National Library of Medicine (NLM) and

�� NonNon--government agencies such as the American government agencies such as the American Legacy Foundation.Legacy Foundation.

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TSEEN Network Referral System

�� LowLow--tar cigarettes cause more cancer than tar cigarettes cause more cancer than regular cigarettes …regular cigarettes …

�� A pressing need for systems that will help A pressing need for systems that will help the TSEEN members effectively connect the TSEEN members effectively connect with other individuals, data sets, analytic with other individuals, data sets, analytic tools, instruments, sensors, documents, tools, instruments, sensors, documents, related to key concepts and issues related to key concepts and issues

Tobacco Behavioral Informatics Grid

(ToBIG)

Network Referral System

�� LowLow--tar cigarettes cause more cancer than tar cigarettes cause more cancer than regular cigarettes …regular cigarettes …

�� A pressing need for systems that will help A pressing need for systems that will help the TSEEN members effectively connect the TSEEN members effectively connect with other individuals, data sets, analytic with other individuals, data sets, analytic tools, instruments, sensors, documents, tools, instruments, sensors, documents, related to key concepts and issues related to key concepts and issues

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Tobacco

Harm Reduction

Tobacco

Cessation

Tool 1

Tool 4

Tool 2

Tool 4

DB 4

DB 3 DB 1

DB 2

Network Map: Example based on prototype developed for

Tobacco Surveillance Evaluation & Epidemiology Network



Communities



Practice (P&G)










Community


Communities)













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CoP Network’s Vital Statistics

�� ScanningScanning

�� AbsorptionAbsorption

�� DiffusionDiffusion

�� RobustnessRobustness

�� VulnerabilityVulnerability

Diagnosis Questions

� How capable at scanning external expertise?

� How capable at absorbing expertise from the

external network to the internal network?

� How efficient at diffusing the external expertise

within the internal network?

� How robust in a specific area of expertise against

disruption?

� How vulnerable to being externally brokered?

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Best scannerBest scanner

Best expert Best expert

scannerscanner

Strongest capacity Strongest capacity

to absorbto absorb

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Most effective Most effective

diffusersdiffusers

Most effective Most effective

diffusersdiffusers

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From Diagnostics to Design

1.1. Network Participants: SocioNetwork Participants: Socio--Technical Technical

Network Referral Systems Network Referral Systems

2.2. Network Managers: Individual, Network Managers: Individual,

Organizational and Social Incentives Organizational and Social Incentives ––

using the Multiusing the Multi--theoretical Multilevel theoretical Multilevel

(MTML) Model(MTML) Model

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Designing CoPs as

Small World Networks

�� Industries with small world network structures are more Industries with small world network structures are more

innovative! innovative!

�� Networks where people spend most of their time Networks where people spend most of their time

communicating with one another in a group (“cluster”) communicating with one another in a group (“cluster”) andand

spend some time communicating with others outside (“short spend some time communicating with others outside (“short

cuts”) cuts”)

�� Small world networks exhibit high levels of “clustering” and Small world networks exhibit high levels of “clustering” and

few “shortcuts”few “shortcuts”

�� Clusters engender trust and control, maximize capability Clusters engender trust and control, maximize capability

for for exploitationexploitation

�� Shortcuts engender unique combinations of network Shortcuts engender unique combinations of network

resources, maximize capacity for resources, maximize capacity for explorationexploration

“Pre-wired” PackEdge CoP Network

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“Re-wired” PackEdge CoP Network

Wiring the PackEdge CoP Network

for Success

Increase the likelihood to give and get information to Increase the likelihood to give and get information to the right target and source respectivelythe right target and source respectively

�� Benefits for Benefits for CoPCoP

�� Increase absorptive capacity from 45.3% to 53.4%Increase absorptive capacity from 45.3% to 53.4%

�� Reduce number of steps for diffusion from 4.3 to 2.6Reduce number of steps for diffusion from 4.3 to 2.6

�� Costs for Costs for CoPCoP

�� Increase communication links of network leaders from Increase communication links of network leaders from 28 to 38 (~ 150 new links).28 to 38 (~ 150 new links).

�� Increase criticality of network leaders from 26.7 % to Increase criticality of network leaders from 26.7 % to 48.5%48.5%

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Summary

�� The The LovegetyLovegety underscore 21underscore 21stst century aspirations for more century aspirations for more effective networking. effective networking.

�� Recent advances in Recent advances in cyberinfrastructure developmentcyberinfrastructure development provides provides the technological capability to more effectively leverage our the technological capability to more effectively leverage our CoPCoP networks.networks.

�� Recent advances in Recent advances in communication networks researchcommunication networks research provides provides important insights into the social and organizational motivationimportant insights into the social and organizational motivations s that explain how we leverage our that explain how we leverage our CoPCoP networks. networks.

�� We are poised for the design, development, and deployment of We are poised for the design, development, and deployment of large scale large scale sociosocio--technical technical CoPCoP network referral systemsnetwork referral systems as part as part of the next generation of the next generation cyberinfrastructurescyberinfrastructures..

Acknowledgements

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Science of Networks in [email protected]

www.uiuc.edu/ph/www/nosh

Diagnosis - Scanning

NL

US

ITBE

US

ITBE

BE

US

US

…

…

Rest of Network

Scanning from many sources (such as countries)

Country codes indicated in nodes

Internal External

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Diagnosis - Absorbent Star

E2

E3

E1

I1

I4

I5

I6

I2

I3

… Rest of

Network

Absorbent

Star

Absorbent star links external experts to internal network

Internal External

Diagnosis - Diffusion

E2

E1 E3

I4

I5

I8

I7I6 ……

I3

I1

I4Isolated

Internal

Pocket

Rest of Network

Internal cluster not connected to the rest of the internal network

Internal External

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Diagnosis - Robustness

E5E4

E3

I2

I3

I6

I5I4 ……

E1

I1

E2

Internal network not robust to loss of I3

Internal External

Diagnosis - Vulnerability

I7

I6

I3

I4

E1

I5

I8

I2I1

ExternalBridge

Internal network vulnerable to external expert E1

Internal External

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Human Agent to Human Agent

Communication

Retrieving from

knowledge repository

Publishing to

knowledge repository

Non Human Agent to

Non Human Agent

Communication

Non Human Agent

(webbots, avatars, databases,

“push” technologies)

To Human Agent

INTERACTION NETWORKS

Source: Contractor, 2001

Human Agent’s Perception of

What Another Human Agent

Knows

Non Human Agent’s

Perception of Resources

in a Non Human Agent

Non Human Agent’s

Perception of what a Human

Agent knows

Human Agent’s Perception of

Provision of Resources in a

Non Human Agent

COGNITIVE KNOWLEDGE NETWORKS

*

* … Why Tivo thinks I am gay and Amazon thinks I am pregnant ….

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CI-KNOW: Harvesting the online

community’s relational meta-data

INPUTS

Cybercommunity

Resources

Cyberinfrastructure

Use

External

Resources

Generating

a Multi-

Dimensional

network

Network

Analysis

PROCESSES

Network

Maps

Network

Referrals

OUTPUTS

Network

Diagnostics

Users’ Profiles

Documents

Collaboration Tools

Datasets

Analysis Tools

Bibliographic DBs

Personal Websites

Organizational

Websites

Project Websites

Patent Databases

Linking all

data together

1. Algorithms to

generate Network Referrals

2. Algorithms to create Network Maps

3. Algorithms to compute Network Diagnostics

User activity logs related

to cyberinfrastructure

Downloading

Presentations

Using Tools to

Analyze Datasets

Using Chats,

Forum

INPUTS

Cybercommunity

Resources

Cyberinfrastructure

Use

External

Resources

Generating

a Multi-

Dimensional

network

Network

Analysis

PROCESSES

Network

Maps

Network

Referrals

OUTPUTS

Network

Diagnostics

1. Who to contact for what topic

2. What tools to use

for what data 3. What dataset to

analyze for what concepts

4. What papers to

read for what keywords

1. What nodes are important for what

relations2. The amount of

scanning, absorption, diffusion,

robustness, vulnerability in a network

CI-KNOW: Harvesting the online

community’s relational meta-data