Title: Noshir Contractor
1From Disasters to WoW Enabling Knowledge
Networks in 21st Century Organizational forms
Noshir Contractor Professor, Departments of
Speech Communication Psychology Director, Age
of Networks Initiative, Center for Advanced
Study Director, Science of Networks in
Communities - National Center for Supercomputing
Applications University of Illinois at
Urbana-Champaign nosh_at_uiuc.edu
2- Turn on power set MODE with MODE button. You
can confirm the MODE you chose as the red
indicator blinks. - Lamp blinks when (someone with) a Lovegety for
the opposite sex set under the same MODE as yours
comes near. - 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.
3Key Takeaways
- Desire for social networking tools to assist
multidisciplinary, interdisciplinary, and
transdisciplinary (MIT) collaboration - Development of multi-theoretical multilevel
(MTML) understandings of why we create, maintain,
dissolve and reconstitute social network links. - Development of tools and algorithms to
Discover, Diagnose, and Design (3D) more
effective social networks - Opportunity to harvest empirical
multi-dimensional network data from recent
efforts on the Grid and Web 2.0. - Opportunity to enable more effective social
networking within the Grid - Challenge to develop MTML 2.0 to explain creation
of links in multidimensional networks
4Aphorisms about Networks
- Social 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.
5Cognitive Knowledge Networks
Source Newsweek, December 2000
6INTERACTION NETWORKS
Non Human Agent to Non Human Agent Communication
Non Human Agent (webbots, avatars, databases,
push technologies) To Human Agent
Publishing to knowledge repository
Retrieving from knowledge repository
Human Agent to Human Agent Communication
Source Contractor, 2001
7COGNITIVE KNOWLEDGE NETWORKS
Non Human Agents Perception of Resources in a
Non Human Agent
Human Agents Perception of Provision of
Resources in a Non Human Agent
Non Human Agents Perception of what a Human
Agent knows
Human Agents Perception of What Another Human
Agent Knows
Why Tivo thinks I am gay and Amazon thinks I
am pregnant .
8Human to Human Interactions and Perceptions
Human to Non Human Interactions and Perceptions
Non Human to Human Interactions and Perceptions
Non Human to Non Human Interactions and
Perceptions
9WHY DO WE CREATE, MAINTAIN, DISSOLVE, AND
RECONSTITUTE OUR COMMUNICATION AND KNOWLEDGE
NETWORKS?
10Social DriversWhy do we create and sustain
networks?
- Theories of self-interest
- Theories of social and resource exchange
- Theories of mutual interest and collective action
- Theories of contagion
- Theories of balance
- Theories of homophily
- Theories of proximity
- Theories of co-evolution
Sources Contractor, N. S., Wasserman, S.
Faust, K. (2006). Testing multi-theoretical
multilevel hypotheses about organizational
networks An analytic framework and empirical
example. Academy of Management Review. Monge, P.
R. Contractor, N. S. (2003). Theories of
Communication Networks. New York Oxford
University Press.
11Structural signatures of MTML
Theories of Self interest
Theories of Exchange
Theories of Balance
Theories of Collective Action
Theories of Homophily
Theories of Cognition
12What Have We Learned About These Network
Mechanisms?
- Research typically looks at only one of these
mechanisms - The outcomes of these mechanisms often contradict
one another - Some mechanisms are studied more often than
others - Most research examines these mechanisms at one
point in time
13Enter ERGM Framework
- Integrating exogenous and endogenous processes
based on multiple theories at multiple levels
leads to many possible realizations of the
network. - The observed network is one realization of the
many possible realizations of the network. - Confirmatory Network Analysis The question of
interest in statistical modeling is whether the
observed network exhibits the theoretically
hypothesized structural tendencies.
14A contextual meta-theory ofsocial drivers for
creating and sustaining communities
15Projects Investigating Social Drivers for
Communities
Business Applications PackEdge Community of
Practice (PG) Vodafone-Ericsson Club
for virtual supply chain management (Vodafone)
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)
Core Research Social Drivers for Creating
Sustaining Communities
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) Second Life (Linden Labs, NCSA)
16Contextualizing Goals of Communities
17Projects Investigating Social Drivers for
Communities
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)
Business Applications PackEdge Community of
Practice (PG) Vodafone-Ericsson Club
for virtual supply chain management (Vodafone)
Core Research Social Drivers for Creating
Sustaining Communities
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) Second Life (Linden Labs, NCSA)
183D Strategy for Enhancing CoP Networks
- Discovery Effectively and efficiently foster
network links from people to other people,
knowledge, and artifacts (data sets/streams,
analytic tools, visualization tools, documents,
etc.). If only we knew what we knew. - Diagnosis Assess the health of CoPs internal
and external networks - in terms of scanning,
absorptive capacity, diffusion, robustness, and
vulnerability to external environment - Design or re-wire networks using social and
organizational incentives (based on social
network research) and network referral systems to
enhance evolving and mature communities.
19PackEdge CoP Vital Statistics
- Exploration
- Scanning Access to expertise external to CoP
- Absorption Ability to absorb expertise external
to CoP - Vulnerability Brokered by members external to
CoP - Exploitation
- Diffusion Ability to diffuse expertise
throughout CoP - Robustness Not relying on few critical CoP
members to keep things together
20Pre-wired PackEdge CoP Network
21Re-wired PackEdge CoP Network
22Wiring the PackEdge CoP Network for Success
- Increase the likelihood to give and get
information to the right target and source
respectively - Benefits for CoP
- Increase absorptive capacity from 45.3 to 53.4
- Reduce number of steps for diffusion from 4.3 to
2.6 - Costs for CoP
- Increase communication links of network leaders
from 28 to 38 ( 150 new links). - Increase criticality of network leaders from 26.7
to 48.5
23FRAMEWORK FOR MTML MODELING OF NETWORK DYNAMICS
1. Extend theories to predict the dynamics of
networks (MTML)
Iterative refinements to theories about network
dynamics
Multi-level hypotheses and concepts to be measured
Generative mechanisms
Competence-based design of Cyberinfrastructure
4. Develop interventions including cyberinfrastru
cture tools to enable networks (CI-IKNOW)
3. Collect/capture longitudinal empirical network
data (KAME/NAME/D2K/Automap)
2. Develop agent-based computational models to
assess and evaluate alternative trajectories
of network dynamics (Repast/Blanche)
Web-based surveys, usage logs, text-mining, and
web-crawling tools to capture network dynamics
5. Statistical methods to empirically validate
networks dynamics predicted by agent based
models based on MTML theories (p /ERGM
techniques using MCMC methods)
Model predictions of networks
24Projects Investigating Social Drivers for
Communities
Business Applications PackEdge Community of
Practice (PG) Vodafone-Ericsson Club
for virtual supply chain management (Vodafone)
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)
Core Research Social Drivers for Creating
Sustaining Communities
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) Second Life (Linden Labs, NCSA)
25ICT Support in Emergency Management Networks
Drawing Analogies from Natural Systems
Project funded by NSF IT-Based Collaboration
Framework for Preparing Against, Responding to,
and Recovering (CP2R) from Disasters Involving
Critical Physical Infrastructures, (2004-2009,
2,370,000). Â
26Natural Communities Honey Bees
At hive unloading
At hive unloading
nectar from A
nectar from B
(H
)
(H
)
Honey Bees (Apis melifera)
A
B
Foraging Model Seeley, 1991
p1
p7
p5
p3
f
A
f
B
x
x
1-f
A
1-f
B
x
x
Following
f
A(1-f
A)
other dances
f
B(1-f
B)
d
x
d
x
(F)
Dancing for A
Dancing for B
(D
)
(D
)
A
B
(1-f
A)(1-f
A)
(1-f
B)(1-f
B)
d
x
d
x
p4
p6
p2
The system evaluates ALL the information, though
individuals evaluate only partial information
f
A
f
B
f
f
Foraging at nectar
Foraging at nectar
source A
source B
(A)
(B)
27From insect colonies to emergency response
teamsClient-Server vs. P2P Network
28Kelips P2P Architecture Introduction
- Two components of Kelips (Gupta et al, 2003)
- Layout of the P2P network
- Maintain the balance between number of links
needed for connecting the nodes in the network in
an efficient manner and the cost of maintaining
these links - Message Dissemination over the P2P network
Gossip - Information of the membership whos currently
active in the network whos in and whos out - Who knows what
Gupta, I., Birman, K., Linga, P., Demers, A.,
Renesse, R. v. (2003). Kelips Building an
efficient and stable P2P DHT through increased
memory and background overhead. Paper presented
at the the 2nd International workshop on
Peer-to-Peer Systems (IPTPS'03), Berkeley, CA.
29Kelips Protocol to Generate P2P Network Layout
- Randomly assign members to k different groups (k
) - For instance, members of a network of size N
100 are assigned to k 10 groups - Randomly create links between members, l outgoing
links for each node (l O(log N)) - For instance, in a network of size N 100, each
node will have l O(2) 4-6 outgoing links
30Limitations of KelipsMTML extensions
- First responders are not likely to trust
information from random others (Hollingshead
Costa, 2005) - Network layout needs to take into account the
social motivations for sharing information among
first responders - The MTML (Multi-Theoretical MultiLevel) Model
(Contractor et al, 2006 Monge Contractor, 2003
) provides a framework to investigate social
motivations for why we create, maintain and
dissolve communication networks
31Network Layout Mechanism
- Social Network Theories Applied
- Theory of Social Exchange (SE)
- Theory of Structural Hole (SH)
- Strategies
- Random Layout
- SE/SH Network Layout
- SESH Network Layout
32Simulation Results
- Repast (Recursive Porous Agent Simulation Toolkit
) - Multi-Agent Computational Modeling Toolkit
33Message Dissemination Comparing the Efficiency
of the Strategies
- Using a random network, 20 out of 1000 nodes can
not access the information. This is consistent
with the high coverage predicted by the original
Kelips model. However the coverage improves
(fewer nodes without messages ) when Kelips is
extended to include social exchange and
structural holes as motivation to choose links. - The number of nodes not able to access the
information decreases as the nodes are more
likely to choose links on the basis of social
exchange rather than structural holes - Further, the number of nodes not able to access
the information is consistently lower when nodes
choose links on the basis of social exchange and
structural holes rather than social exchange or
structural holes
34Message Dissemination Comparing the Robustness
of the Strategies
- The robustness improves (fewer nodes without
messages ) when Kelips is extended to include
social exchange and structural holes as
motivation to choose links. - Further, the number of nodes not able to access
the information is consistently lower when nodes
choose links on the basis of social exchange and
structural holes rather than social exchange or
structural holes
35Projects Investigating Social Drivers for
Communities
Business Applications PackEdge Community of
Practice (PG) Vodafone-Ericsson Club
for virtual supply chain management (Vodafone)
Science Applications CLEANER Collaborative
Large Engineering Analysis Network for
Environmental Research (NSF) Collaboration
for Preparedness, Response Recovery
(NSF) TSEEN Tobacco Surveillance Evaluation
Epidemiology Network (NSF, NIH, CDC)
Core Research Social Drivers for Creating
Sustaining Communities
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) Second Life (Linden Labs, NCSA)
36WoW Massively Multiplayer Online Role Playing
Game
37Rise of WoW
Source http//www.mmogchart.com/
38Goals of WoW Community
- Teams perform diverse quests within the game
environment, typically varying in length from one
hour to several days, with the goal of achieving
an objective, gaining resources, and increasing
experience. - Exploiting, Bonding Swarming
39Contextualizing Goals of WoW
40Mapping Goals to Theories WoW Gaming Community
41Data Collection
- Data were collected from all 184 individuals who
belonged to 16 guilds at 3 points in time. - T1 initial contact and survey administration
- T2 two weeks after initial survey administration
- T3 four weeks after initial survey
administration - Demographic information
- Gender
- Female members (21.7)
- Male members (78.3)
- Ethnicity
- Caucasian (79.3)
- Asian/ Pacific Islander (15.2)
- African American (2.2)
- Hispanic/Latino (1.1)
- Native American (1.1)
42Information Retrieval - Time One
43Information Retrieval - Time Two
44Information Retrieval -Time Three
45Density of Communication Ties Decreases over Time
46Unraveling the Structural Signatures
- Incentive for creating a WoW link with someone
- -1.08 (cost of creating a link)
Self-interest - 0.29 (benefit of reciprocating) Exchange
- 3.07 (benefit for being a friend of a friend)
- Balance
- 0.04 (benefit of connecting to an expert)
- Cognition
All coefficients significant at 0.05 level
47Summary
- Theories about the social motivations for
creating, maintaining, dissolving and re-creating
social network ties in multidimensional networks - Development of cyberinfrastructure/Web 2.0
provide the technological capability to capture
relational metadata needed to more effectively
understand (and enable) communities. - Computational modeling techniques to model
multidimensional network dynamics. - Exponential random graph modeling techniques to
empirically validate the local structural
signatures that explain emergent global network
properties
48SONIC Research Team Members
Andy Don Research Programmer NCSA, UIUC
Steven Harper Postdoc NCSA, UIUC
Hank Green Research Scientist NCSA, UIUC
Alex Yahja Postdoc NCSA, UIUC
Nat Bulkley Postdoc NCSA, UIUC
Chunke Su Graduate Research Assistant Speech
Communication, UIUC
Mengxiao Zhu Graduate Research Assistant Speech
Communication, UIUC
York Yao Research Programmer NCSA, UIUC
Diana Jimeno-Ingrum Graduate Research
Assistant Labor Industrial Relations, UIUC
Annie Wang Graduate Research Assistant Speech
Communication, UIUC
49Acknowledgements