Noshir ContractorJane S. & William J. White Professor of Behavioral SciencesJane S. & William J. White Professor of Behavioral SciencesProfessor 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 [email protected] Understanding & Enabling Networks in 21stCentury Organizational FormsSONICAdvancing the Science of Networks OUTLINE• Multilevel motivations for creating, maintaining, dissolving, and reconstituting social and knowledge network links.• Opportunity for 3D approach to networks: Discovery, Diagnosis, & Design in STEM• Other Examples: Tobacco research, nanoHub, CI-ScopeSONICAdvancing the Science of NetworksAphorisms 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.SONICAdvancing the Science of Networks Cognitive Knowledge NetworksSONICAdvancing the Science of NetworksMultidimensional Networks in Web 2.0Multiple Types of Nodes and Multiple Types of RelationshipsMultidimensional Networks in STEMMultiple Types of Nodes and Multiple Types of RelationshipsWHY DO WE CREATE, MAINTAIN, DISSOLVE, AND RECONSTITUTE OUR COMMUNICATION AND KNOWLEDGE NETWORKS?SONICAdvancing the Science of NetworksMonge, P. R. & Contractor, N. S. (2003). Theories of Communication Networks. New York: Oxford University Press.SONICAdvancing the Science of Networks Social Drivers:Why 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-evolutionSources: 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.SONICAdvancing the Science of NetworksBFCAED- + BF CAED- + B FCAED+ FEDBCA- + Government Industry FEDBCA- +Novice Expert “Structural signatures” of MTMLTheories of Self interest Theories of ExchangeTheories of Collective ActionTheories of BalanceTheories of Homophily Theories of CognitionSONICAdvancing the Science of Networks Statistical “MRI” for Structural Signatures• ERGM: Exponential Random Graph Models• Statistical “Macro-scope” to detect structural motifs in observed networks• Move from exploratory to confirmatory network analysis to understand multi-theoretical multilevel motivations for why we create our social networksSONICAdvancing the Science of NetworksEmpirical IllustrationCo-evolution of knowledge networks and 21stcentury organizational formsn NSF KDI Initiative, PI: Noshir Contractorn Co-P.I.s: Bar, Fulk, Hollingshead, Monge (USC), Kunz, Levitt (Stanford), Carley (CMU), Wasserman (Indiana).n Three dozen industry partners (global, profit, non-profit): u Boeing, 3M, NASA, Fiat, U.S. Army, American Bar Association, European Union Project Team, Pew Internet Project, etc.SONICAdvancing the Science of Networks Transactive Memoryu Perception of Other’s Knowledgeu Communication to Allocate Information Social Exchange- Retrieval by coworkers onothertopicsPublic Goods / Transactive Memory–Allocation to the Intranet–Retrieval from the Intranet–Perceived Quality and Quantity of Contribution to the IntranetInertia Components–Collaboration–Co-authorship–CommunicationCommunication to Retrieve InformationProximity-Work in the same locationSONICAdvancing the Science of Networks1. Social Communication 0.1442. Perception of Knowledge & Communication to Allocate 0.9953. Perception of Knowledge & Provision 0.9724. Perception of Knowledge, Social Exchange, & Social Communication 0.8515. Perception of Knowledge, Proximity, & Social Communication 0.882Multi-theoretical p*/ERGMTheoretical Predictors of CRISONICAdvancing the Science of Networks 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 communitiesSONICAdvancing the Science of NetworksCore ResearchSocial Drivers for Creating & Sustaining CommunitiesBusiness ApplicationsPackEdge Community of Practice (P&G)Vodafone-Ericsson “Club” for virtual supply chain management (Vodafone)Societal Justice ApplicationsCultural & Networks AssetsIn Immigrant Communities (Rockefeller Program on Culture & Creativity)Mapping the Digital Media and Learning Environment (MacArthur Foundation)Entertainment ApplicationsSecond Life (Linden Labs)Everquest 2 (NSF, Sony Online Entertainment)Science ApplicationsNano-IKNOW: Enabling and Evaluating the Network for Computational Nanotechnology (NSF)CP2R: Collaboration for Preparedness,Response & Recovery (NSF)TSEEN: Tobacco Surveillance Evaluation & Epidemiology Network (NSF, NIH, CDC)Projects Investigating Social Drivers for CommunitiesSONICAdvancing the Science of Networks 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 CommunitiesChallenges of empirically testing, extending, and exploring theories about networks … until nowSONICAdvancing the Science of NetworksIts all about “Relational Metadata”• Technologies that “capture” communities’ relational meta-data (Pingback and trackback in interblog networks, blogrolls, data provenance)• Technologies to “tag” communities’ relational metadata (from Dublin Core taxonomies to folksonomies (‘wisdom of crowds’) like – Tagging pictures