noshir contractor jane s. & william j. white professor of behavioral sciences jane s. &...
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Noshir ContractorJane S. & William J. White Professor of Behavioral SciencesJane S. & William J. White Professor of Behavioral Sciences
Professor of Ind. Engg & Mgmt Sciences, McCormick School of Engineering Professor of Communication Studies, School of Communication &
Professor of Management & Organizations, Kellogg School of Management,Director, Science of Networks in Communities (SONIC) Research Laboratory
Supported by NSF : OCI-0753047, IIS-0729505, IIS-0535214, SBE-0555115
From Disasters to WoW: Enabling Knowledge Networks in the 21st century
SONIC
Advancing the Science of Networks in Communities
Each circle (node) represents one person in the data set. There are 2200
persons in this subcomponent of the social network. Circles with red borders
denote women, and circles with blue borders denote men. The size of each
circle is proportional to the person's body-mass index. The interior color of the
circles indicates the person's obesity status: yellow denotes an obese
person(body-mass index, 30) and green denotes a non-obese person. The
colors of the ties between the nodes indicate the relationship between them:
purple denotes a friendship or marital tie and orange denotes a familial tie.
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.
SONIC
Advancing the Science of Networks in Communities
Cognitive Knowledge Networks
SONIC
Advancing the Science of Networks in Communities
Multidimensional Networks in Web 2.0Multiple Types of Nodes and Multiple Types of Relationships
SONIC
Advancing the Science of Networks in Communities
WHY DO WE CREATE,
MAINTAIN, DISSOLVE, AND
RECONSTITUTE OUR COMMUNICATION AND
KNOWLEDGE NETWORKS?
SONIC
Advancing the Science of Networks in Communities
Social Drivers:Why do we create and sustain
networks? Theories of self-Theories 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 co-Theories of co-
evolutionevolutionSources: 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.
SONIC
Advancing the Science of Networks in Communities
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” ofsocial drivers for creating and sustaining
communities
SONIC
Advancing the Science of Networks in Communities
Core Research
Social Drivers for Creating & Sustaining
Communities
Business Applications
PackEdge Community of Practice (P&G)
Societal Justice Applications
Cultural & Networks AssetsIn Immigrant Communities (Rockefeller Program on Culture & Creativity)
Mapping Digital Media and Learning Networks(MacArthur Foundation)
Entertainment Applications
Virtual Worlds Exploratorium (NSF, Sony Online Entertainment, Linden Labs)
Science ApplicationsCI-Scope: Understanding & Enabling CI in Virtual Communities (NSF)
CP2R: Collaboration for Preparedness,Response & Recovery (NSF)
TSEEN: Tobacco Surveillance Evaluation & Epidemiology Network (NSF, NIH, CDC)
Projects Investigating Social Drivers for Communities
SONIC
Advancing the Science of Networks in Communities
Exploring Exploiting Mobilizing Bonding Swarming
Emergency Response Community
+ + +
WoW Gaming Community + + + Mexican Immigrant
Community + +
PackEdge Communities of Practice
+ + +
Economic Resilience NGO Community
+ +
Tobacco Surveillance, Evaluation & Epidemiology
Community + +
Environmental Engineering Community
+ + +
Contextualizing Goals of Communities
Challenges of empirically testing, extending, and exploring theories about networks … until now
SONIC
Advancing the Science of Networks in Communities
Enter Semantic Web/Web 2.0Its all about “Relational Metadata”
Technologies that “Technologies that “capturecapture” communities’ relational meta-data ” communities’ relational meta-data (Pingback and trackback in interblog networks, blogrolls, data (Pingback and trackback in interblog networks, blogrolls, data provenance)provenance)
Technologies to “Technologies to “tagtag” communities’ relational metadata (from Dublin ” communities’ relational metadata (from Dublin Core taxonomies to folksonomies (‘wisdom of crowds’) like Core taxonomies to folksonomies (‘wisdom of crowds’) like Tagging pictures (Flickr)Tagging pictures (Flickr) Social bookmarking (del.icio.us, LookupThis, BlinkList)Social bookmarking (del.icio.us, LookupThis, BlinkList) Social citations (CiteULike.org)Social citations (CiteULike.org) Social libraries (discogs.com, LibraryThing.com)Social libraries (discogs.com, LibraryThing.com) Social shopping (SwagRoll, Kaboodle, thethingsiwant.com)Social shopping (SwagRoll, Kaboodle, thethingsiwant.com) Social networks (FOAF, XFN, MySpace, Facebook)Social networks (FOAF, XFN, MySpace, Facebook)
Technologies to “Technologies to “manifestmanifest” communities’ relational metadata ” communities’ relational metadata (Tagclouds, Recommender systems, Rating/Reputation systems, ISI’s (Tagclouds, Recommender systems, Rating/Reputation systems, ISI’s HistCite, Network Visualization systems)HistCite, Network Visualization systems)
SONIC
Advancing the Science of Networks in Communities
Text Mining Web crawlingWeb of Science Citation
CATPAC
UBERLINK
Digital Harvesting of Relational Metadata
CI-KNOW Analyses and Visualizations SONIC
Advancing the Science of Networks in Communities
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 DBsPersonal WebsitesOrganizational
WebsitesProject WebsitesPatent 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
SONIC
Advancing the Science of Networks in Communities
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 relations
2. The amount of scanning, absorption, diffusion, robustness, vulnerability in a network
CI-KNOW: Harvesting the online community’s relational meta-data
SONIC
Advancing the Science of Networks in Communities
Core Research
Social Drivers for Creating & Sustaining
Communities
Business Applications
PackEdge Community of Practice (P&G)
Societal Justice Applications
Cultural & Networks AssetsIn Immigrant Communities (Rockefeller Program on Culture & Creativity)
Mapping Digital Media and Learning Networks(MacArthur Foundation)
Entertainment Applications
Virtual Worlds Exploratorium (NSF, Sony Online Entertainment, Linden Labs)
Science ApplicationsCI-Scope: Understanding & Enabling CI in Virtual Communities (NSF)
CP2R: Collaboration for Preparedness,Response & Recovery (NSF)
TSEEN: Tobacco Surveillance Evaluation & Epidemiology Network (NSF, NIH, CDC)
Projects Investigating Social Drivers for Communities
SONIC
Advancing the Science of Networks in Communities
Hurricane Katrina 2005Formed:Formed: Aug 23, 2005Aug 23, 2005Dissipated:Dissipated: Aug 31, 2005Aug 31, 2005Highest wind:Highest wind: 175 mph175 mphLowest press:Lowest press: 902 mbar902 mbarDamages:Damages: $81.2 Billion$81.2 BillionFatalities:Fatalities: >1,836>1,836Areas affected:Areas affected: Bahamas,Bahamas, South Florida, South Florida,
Cuba, Louisiana Cuba, Louisiana (especially (especially Greater New Greater New Orleans), Orleans), Mississippi, Mississippi, Alabama, Alabama, Florida Florida Panhandle, most Panhandle, most of eastern North of eastern North AmericaAmerica
Map source: http://hurricane.csc.noaa.gov/
8/23
8/24
8/25
8/268/27
8/28
8/29
8/30
8/31
SONIC
Advancing the Science of Networks in Communities
SITREP Content
Basic Format / InformationBasic Format / Information1.1. Situation (What, Where, and When)Situation (What, Where, and When)
2.2. Action in ProgressAction in Progress
3.3. Action PlannedAction Planned
4.4. Probable Support Requirements and/or Probable Support Requirements and/or Support AvailableSupport Available
5.5. Other itemsOther items
SONIC
Advancing the Science of Networks in Communities
Typical SITREP *Colorado Division of Emergency Management SITUATION REPORT 2005-6 (Hurricane Katrina) August 30, 2005*
*Event Type:* Hurricane Response
*Situation:* On August 29, Hurricane Katrina hit the gulf coast east of NewOrleans. It was considered a Category 5 Hurricane, which brings winds ofover 155mph and storm surge of 18 feet above normal. Massive property damagehas occurred and undetermined number of deaths and injuries.
Colorado response to date include two deployments:- Two members from the Division of Emergency Management to the Louisiana EOC, departed on August 29. · · ·
*Weather Report:* Katrina is moving toward the north-northeast near 18 mph.A turn toward the northeast and a faster forward speed is expected duringthe next 24 hours. This motion should bring the cent · · ·
*Agencies Involved:* Colorado Department of Military and Veteran Affairs,Department of Local Affairs, Division of Emergency Management, Governor'sOffice.* *
*Additional Assistance Requested:* Type III teams, consisting of Operations,Plans, and Logistics personnel (two individuals for each area). These teamscould deploy to Alabama, Louisiana, and/or Mississippi. Teams will beat either working the State or Parish/County EOCs. · · ·
SONIC
Advancing the Science of Networks in Communities
Human Coding Procedure
Using an HTML editor to mark entities Using an HTML editor to mark entities (people, organizations, locations, concepts)(people, organizations, locations, concepts)
as bold and include a unique HTML tag as bold and include a unique HTML tag
<b><a name=“F10005505a00003”></a>FEMA</b><b><a name=“F10005505a00003”></a>FEMA</b>
SONIC
Advancing the Science of Networks in Communities
Automatic Coding D2K – The Data to Knowledge application D2K – The Data to Knowledge application
environment is a rapid, flexible data mining environment is a rapid, flexible data mining and machine learning systemand machine learning system
Automated processing is done through Automated processing is done through creating itineraries that combine processing creating itineraries that combine processing modules into a workflowmodules into a workflow
Developed by the Developed by the
Automated LearningAutomated Learning
Group at NCSAGroup at NCSA SONIC
Advancing the Science of Networks in Communities
Time Slice 1: 8/23 to 8/25/2005
ARCSAL
FEMA
Shelter
TX
KY
AL
LA
NO
Gov Bush
FL
Petroleum Network formed Early
Florida is the Topicof the Conversation
SONIC
Advancing the Science of Networks in Communities
Time Slice 1 to 2
ARCSAL
FEMA
Shelter
TX
KY
AL
LA
NO
Gov Bush
FL
Power
FP&L
GA
Military
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Advancing the Science of Networks in Communities
Time Slice 2: 8/26 to 8/27/2005
ARC
SAL
FEMA
Shelter
TXMSLA
NO
Gov Bush
FL Power
FP&L
GA
Military
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Advancing the Science of Networks in Communities
Time Slice 2 to 3
ARC
SAL
FEMA
Shelter
TXMSLA
NO
Gov Bush
FL
Power
FP&L
GA
Military
NC
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Advancing the Science of Networks in Communities
Time Slice 3: 8/28 to 8/29/2005
ARC
FEMA
Shelter
TX
MS LA
NO
Gov Bush
FL
PowerFP&L
NC
Military
GA
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Advancing the Science of Networks in Communities
Time Slice 3 to 4
ARC
FEMA
Shelter
TX
MS LA
NO
Gov Bush
FL
PowerFP&L
NC
Military
GA
AL Power
S & R
National Guard
AL
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Advancing the Science of Networks in Communities
Time Slice 4: 8/30 to 8/31/2005
ARC
FEMA
Shelter
TX
MS
LA
NO
FLPower
FP&LNC
GA
AL Power
S & R
National Guard
AL
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Advancing the Science of Networks in Communities
Time Slice 4 to 5
ARC
FEMA
Shelter
TX
LA
NO
FLPower
FP&LNC
GA
AL Power
S & R
National Guard
MS
AL
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Advancing the Science of Networks in Communities
Time Slice 5: 9/1 to 9/2/2005
ARC
FEMA
Shelter
TX
MS LA
NO
FL
Power
NC
GA
AL Power
S & R
National Guard
AL
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Advancing the Science of Networks in Communities
Time Slice 5 to 6
ARC
FEMA
Shelter
TX
MS LA
NO
FL
Power
GA
AL Power
S & R
National Guard
AL
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Advancing the Science of Networks in Communities
Time Slice 6: 9/3 to 9/4/2005
ARC
FEMA
Shelter
TX
MS
LA
NO
FL
OutagesGA
AL Power
Urban S & R
National Guard
AL
S & R
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Advancing the Science of Networks in Communities
Betweeness Centrality
0
50
100
150
200
250
1 2 3 4 5 6 7
Time Slice
Ran
k
American Red Cross FEMA
Change in Network Centrality Rankings
• “American Red Cross” starts in the 200s and moves to the teens• “FEMA” starts in the 20s, moves to the teens, and ends in the 60s
FEMA drops rank and American Red Cross moves up
Crossover where American Red Cross becomes relatively more central than FEMA (Sep 1, 2005)
SONIC
Advancing the Science of Networks in Communities
Core Research
Social Drivers for Creating & Sustaining
Communities
Business Applications
PackEdge Community of Practice (P&G)
Societal Justice Applications
Cultural & Networks AssetsIn Immigrant Communities (Rockefeller Program on Culture & Creativity)
Mapping Digital Media and Learning Networks(MacArthur Foundation)
Entertainment Applications
Virtual Worlds Exploratorium (NSF, Sony Online Entertainment, Linden Labs)
Science ApplicationsCI-Scope: Understanding & Enabling CI in Virtual Communities (NSF)
CP2R: Collaboration for Preparedness,Response & Recovery (NSF)
TSEEN: Tobacco Surveillance Evaluation & Epidemiology Network (NSF, NIH, CDC)
Projects Investigating Social Drivers for Communities
SONIC
Advancing the Science of Networks in Communities
3D Strategy for Enhancing Knowledge Networks
DDiscoveryiscovery: Effectively and efficiently foster network links : Effectively and efficiently foster network links from people to other people, knowledge, and artifacts from people to other people, knowledge, and artifacts (data sets/streams, analytic tools, visualization tools, (data sets/streams, analytic tools, visualization tools, documents, etc.) documents, etc.) ““If only If only NSFNSF knows what knows what NSF NSF knows”.knows”.
DDiagnosisiagnosis: Assess the “health” of internal and external : Assess the “health” of internal and external networks - in terms of scanning, absorptive capacity, networks - in terms of scanning, absorptive capacity, diffusion, robustness, and vulnerability to external diffusion, robustness, and vulnerability to external environmentenvironment
DDesignesign: Model or re-wire networks using social and : Model or re-wire networks using social and organizational incentives (based on social network organizational incentives (based on social network research) and network referral systems to enhance research) and network referral systems to enhance evolving and mature communitiesevolving and mature communities
SONIC
Advancing the Science of Networks in Communities
“Discovery” Problems in Knowledge Networks
IDC found Fortune 500 companies lose $31.5 billion annually due IDC found Fortune 500 companies lose $31.5 billion annually due to rework and the inability to find information. to rework and the inability to find information.
The Delphi Consulting Group found that:The Delphi Consulting Group found that: Only 12 percent of a typical company's knowledge is explicitly
published. Remaining 88 percent is ‘distributed knowledge’, comprised of employees' personal knowledge.
Up to 42 percent of knowledge professionals need to do their jobs comes from other people's brains - in the form of advice, opinions, judgment, or answers. More often than not, much of this exchange does not follow channels displayed in an organizational chart.
SONIC
Advancing the Science of Networks in Communities
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?
SONIC
Advancing the Science of Networks in Communities
Goal of Discovery – “IKNOW”
SONIC
Advancing the Science of Networks in Communities
“Diagnosis”: Why Diagnose the Network?
Naturally occurring networks are not Naturally occurring networks are not
always efficient or fully functionalalways efficient or fully functional
Gaps, isolates, lack or difficulty of connectivity
Network measures can be used to Network measures can be used to diagnose network’s vital statisticsdiagnose network’s vital statistics
SONIC
Advancing the Science of Networks in Communities
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?
SONIC
Advancing the Science of Networks in Communities
Strongest Strongest capacity to capacity to
absorbabsorb
From Diagnosis to “Design”
1.1. Identifying which network links need to Identifying which network links need to be “re-wired” optimize the collective be “re-wired” optimize the collective power of the network.power of the network.
2.2. Identifying the Individual, Identifying the Individual, Organizational and Social Incentives – Organizational and Social Incentives – for members to want to re-wire.for members to want to re-wire.
SONIC
Advancing the Science of Networks in Communities
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 spend some time communicating with others outside (“short cuts”) outside (“short cuts”)
Small world networks exhibit high levels of “clustering” Small world networks exhibit high levels of “clustering” and few “shortcuts”and few “shortcuts”
Clusters engender trust and control, maximize Clusters engender trust and control, maximize capability for capability for exploitationexploitation
Shortcuts engender unique combinations of network Shortcuts engender unique combinations of network resources, maximize capacity for resources, maximize capacity for explorationexploration
SONIC
Advancing the Science of Networks in Communities
“Pre-wired” PackEdge CoP Network
“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 CoPBenefits for CoP 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 CoPCosts for CoP 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%
SONIC
Advancing the Science of Networks in Communities
Core Research Social Drivers for
Creating & Sustaining Communities
Business Applications
PackEdge Community of Practice (P&G)
Vodafone-Ericsson “Club” for virtual supply chain management (Vodafone)
Kraft Product Design Teams
Societal Justice Applications
Cultural & Networks AssetsIn Immigrant Communities (Rockefeller Program on Culture & Creativity)
Digital Media and Learning(MacArthur Foundation)
Entertainment Applications
World of Warcraft (NSF)
Everquest (NSF, ARI, Sony Online Entertainment)
Second Life (Linden Labs)INFORMS paper by Yun Huang et al
Science Applications
VOSS: Virtual Organizations as Socio-technical Systems (NSF)
CP2R: Collaboration for Preparedness,Response & Recovery (NSF) INFORMS paper by Mengxiao Zhu et al
TSEEN: Tobacco Surveillance Evaluation & Epidemiology Network (NSF, NIH, CDC)
Projects Investigating Social Drivers for Communities
SONIC
Advancing the Science of Networks in Communities
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Advancing the Science of Networks in Communities
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Advancing the Science of Networks in Communities
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Advancing the Science of Networks in Communities
Source: http://www.mmogchart.com/
Rise of WoW
SONIC
Advancing the Science of Networks in Communities
Expertise/Information Retrieval Time One
Expertise/Information Retrieval Time Two
Expertise/Information Retrieval Time Three
Unraveling the “Structural Signatures”
Incentive for creating a WoW link with Incentive for creating a WoW link with someone someone
= -1.55 (cost of creating a link) = -1.55 (cost of creating a link) [Self-interest][Self-interest]
+ 0.55 (benefit of reciprocating) + 0.55 (benefit of reciprocating) [Exchange][Exchange]
+ 0.89 (benefit for being a friend of a friend)+ 0.89 (benefit for being a friend of a friend)
[Balance][Balance]
+ 0.04 (benefit of connecting to an expert) + 0.04 (benefit of connecting to an expert) [Cognition][Cognition]
All coefficients significant at 0.05 level
SONIC
Advancing the Science of Networks in Communities
Tobacco Research: TobIG Demo
Computational Nanotechnology: nanoHUB Demo
Cyberinfrastructure: CI-Scope Demo
Oncofertility: Onco-IKNOW
Design Examples: Mapping & Enabling Networks in …
SONIC
Advancing the Science of Networks in Communities
Summary Research on the dynamics of networks is well poised to make a Research on the dynamics of networks is well poised to make a
quantum intellectual leap by facilitating collaboration that quantum intellectual leap by facilitating collaboration that leverages recent advances in:leverages recent advances in:
Theories about the social motivations for creating, maintaining, Theories about the social motivations for creating, maintaining, dissolving and re-creating social network tiesdissolving and re-creating social network ties
Development of cyberinfrastructure/Web 2.0Development of cyberinfrastructure/Web 2.0 provide the provide the technological capability to capture relational metadata needed to technological capability to capture relational metadata needed to more effectively understand (and enable) communities.more effectively understand (and enable) communities.
Exponential random graph modeling techniques to make Exponential random graph modeling techniques to make theoretically grounded network recommendations that go beyond theoretically grounded network recommendations that go beyond the Lovegety and SNIFthe Lovegety and SNIF
SONIC
Advancing the Science of Networks in Communities
SONIC Team members
Zack JohnsonUndergrad, SONIC
Sanjeev JhaDoctoral candidate, SONIC
Jinling LiResearch Programmer, SONIC
York YaoResearch Programmer, SONIC
Yun HuangPost-doc, SONIC
SONIC
Advancing the Science of Networks in Communities
Acknowledgements
SONIC
Advancing the Science of Networks in Communities