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Noshir Contractor Jane S. & William J. White Professor of Behavioral Sciences Jane S. & William J. White Professor of Behavioral Sciences Professor of.

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1 Noshir Contractor Jane S. & William J. White Professor of Behavioral Sciences Jane 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 nosh@northwestern.edu Supported by NSF : OCI-0753047, IIS-0729505, IIS-0535214, SBE-0555115 Web Science: An Exploratorium for Understanding and Enabling Social Networks SONIC Advancing the Science of Networks in Communities

2 Key Takeaways n Web Science is well poised to make a quantum intellectual leap by facilitating collaboration that leverages recent advances in: u Theories: Theories about the social motivations for creating, maintaining, dissolving and re-creating links in multidimensional networks. Generative mechanisms for emergence of macro-structures. u Data: Developments in Semantic Web/Web 2.0 provide the technological capability to capture, store, merge, and query relational metadata needed to more effectively understand and enable communities. u Methods: An ensemble of qualitative and quantitative methods (exponential random graph modeling (p*) techniques to understand and enable theoretically grounded network recommendations u Computational infrastructure: Cloud computing and petascale applications are critical to face the computational challenges in analyzing the data SONIC Advancing the Science of Networks in Communities

3 Emergent Structures in the Blogosphere by Language SONIC Advancing the Science of Networks in Communities Source; John Kelly

4 WHAT ARE THE GENERATIVE MECHANISMS THAT EXPLAIN THE EMERGENT STRUCTURES OBSERVED IN LARGE SCALE NETWORKS? WEB SCIENCE PROCESS MODEL SONIC Advancing the Science of Networks in Communities

5 Generative Mechanisms: Why do we create and sustain networks? nTheories of self- interest nTheories of social and resource exchange nTheories of mutual interest and collective action nTheories of contagion nTheories of balance nTheories of homophily nTheories of proximity nTheories 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. SONIC Advancing the Science of Networks in Communities

6 F E D B C A -+ Novice Expert “Structural signatures” Theories of Self interestTheories of Exchange Theories of Collective Action Theories of Balance Theories of HomophilyTheories of Cognition SONIC Advancing the Science of Networks in Communities

7 Statistical “MRI” for Structural Signatures p*/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 networks SONIC Advancing the Science of Networks in Communities

8 A contextual “meta-theory” of social drivers for creating and sustaining communities SONIC Advancing the Science of Networks in Communities

9 Core Research Socio-technical Drivers for Creating & Sustaining Communities Business Applications PackEdge Community of Practice (P&G) Kraft Design Teams Societal Justice Applications Cultural & Networks Assets In Immigrant Communities (Rockefeller Program on Culture & Creativity) Mapping Digital Media and Learning Networks (MacArthur Foundation) Science Applications CI-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 Entertainment Applications Second Life (NSF, Army Research Institute, Linden Labs) EverQuest II (NSF, Army Research Institute, Linden Labs)

10 Contextualizing Goals of Communities Challenges of empirically testing, extending, and exploring theories about networks … until now SONIC Advancing the Science of Networks in Communities

11 Multidimensional Networks in the Semantic Web/Web 2.0 Multiple Types of Nodes and Multiple Types of Relationships SONIC Advancing the Science of Networks in Communities

12 Its all about “Relational Metadata” nTechnologies that “capture” communities’ relational meta-data (Pingback and trackback in interblog networks, blogrolls, data provenance) nTechnologies to “tag” communities’ relational metadata (from Dublin Core taxonomies to folksonomies (‘wisdom of crowds’) like uTagging pictures (Flickr) uSocial bookmarking (del.icio.us, LookupThis, BlinkList) uSocial citations (CiteULike.org) uSocial libraries (discogs.com, LibraryThing.com) uSocial shopping (SwagRoll, Kaboodle, thethingsiwant.com) uSocial networks (FOAF, SIOC, SocialGraph) nTechnologies to “manifest” communities’ relational metadata (Tagclouds, Recommender systems, Rating/Reputation systems, ISI’s HistCite, Network Visualization systems) SONIC Advancing the Science of Networks in Communities

13 The Hubble telescope: $2.5 billion SONIC Advancing the Science of Networks in Communities Source: David Lazer

14 CERN particle accelerator: $1 billion/year SONIC Advancing the Science of Networks in Communities Source: David Lazer

15 The Web: priceless * Source: David Lazer * Apologies to MasterCard SONIC Advancing the Science of Networks in Communities

16 SONIC Advancing the Science of Networks in Communities

17 Bios, titles & descriptions Personal Web sites Google search results Web of Science Citation CATPAC UBERLINK Digital Harvesting of Relational Metadata CI-KNOW Analyses and Visualizations SONIC Advancing the Science of Networks in Communities

18 Core Research Socio-technical Drivers for Creating & Sustaining Communities Business Applications PackEdge Community of Practice (P&G) Kraft Design Teams Societal Justice Applications Cultural & Networks Assets In Immigrant Communities (Rockefeller Program on Culture & Creativity) Mapping Digital Media and Learning Networks (MacArthur Foundation) Science Applications CI-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 Entertainment Applications Second Life (NSF, Army Research Institute, Linden Labs) EverQuest II (NSF, Army Research Institute, Linden Labs) SONIC Advancing the Science of Networks in Communities

19 Hurricane Katrina 2005 Formed:Aug 23, 2005 Dissipated:Aug 31, 2005 Highest wind:175 mph Lowest press:902 mbar Damages:$81.2 Billion Fatalities:>1,836 Areas affected:Bahamas, South Florida, Cuba, Louisiana (especially Greater New Orleans), Mississippi, Alabama, Florida Panhandle, most of eastern North America Map source: http://hurricane.csc.noaa.gov/ 8/23 8/24 8/25 8/26 8/27 8/28 8/29 8/30 8/31 SONIC Advancing the Science of Networks in Communities

20 SITREP Content nBasic Format / Information 1.Situation (What, Where, and When) 2.Action in Progress 3.Action Planned 4.Probable Support Requirements and/or Support Available 5.Other items SONIC Advancing the Science of Networks in Communities

21 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 New Orleans. It was considered a Category 5 Hurricane, which brings winds of over 155mph and storm surge of 18 feet above normal. Massive property damage has 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 during the 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's Office.* * *Additional Assistance Requested:* Type III teams, consisting of Operations, Plans, and Logistics personnel (two individuals for each area). These teams could deploy to Alabama, Louisiana, and/or Mississippi. Teams will be at either working the State or Parish/County EOCs. · · · SONIC Advancing the Science of Networks in Communities

22 Human Coding Procedure nUsing an HTML editor to mark entities (people, organizations, locations, concepts) u as bold and include a unique HTML tag u FEMA SONIC Advancing the Science of Networks in Communities

23 Automatic Coding nD2K – The Data to Knowledge application environment is a rapid, flexible data mining and machine learning system nAutomated processing is done through creating itineraries that combine processing modules into a workflow nDeveloped by the Automated Learning Group at NCSA SONIC Advancing the Science of Networks in Communities

24 Time Slice 1: 8/23 to 8/25/2005 ARC SAL FEMA Shelter TX KY AL LA NO Gov Bush FL Petroleum Network formed Early Florida is the Topic of the Conversation SONIC Advancing the Science of Networks in Communities

25 Time Slice 1 to 2 ARC SAL FEMA Shelter TX KY AL LA NO Gov Bush FL Power FP&L GA Military SONIC Advancing the Science of Networks in Communities

26 Time Slice 2: 8/26 to 8/27/2005 ARC SAL FEMA Shelter TX MS LA NO Gov Bush FL Power FP&L GA Military SONIC Advancing the Science of Networks in Communities

27 Time Slice 2 to 3 ARC SAL FEMA Shelter TX MS LA NO Gov Bush FL Power FP&L GA Military NC SONIC Advancing the Science of Networks in Communities

28 Time Slice 3: 8/28 to 8/29/2005 ARC FEMA Shelter TX MS LA NO Gov Bush FL Power FP&L NC Military GA SONIC Advancing the Science of Networks in Communities

29 Time Slice 3 to 4 ARC FEMA Shelter TX MS LA NO Gov Bush FL Power FP&L NC Military GA AL Power S & R National Guard AL SONIC Advancing the Science of Networks in Communities

30 Time Slice 4: 8/30 to 8/31/2005 ARC FEMA Shelter TX MS LA NO FL Power FP&L NC GA AL Power S & R National Guard AL SONIC Advancing the Science of Networks in Communities

31 Time Slice 4 to 5 ARC FEMA Shelter TX LA NO FL Power FP&L NC GA AL Power S & R National Guard MS AL SONIC Advancing the Science of Networks in Communities

32 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 SONIC Advancing the Science of Networks in Communities

33 Time Slice 5 to 6 ARC FEMA Shelter TX MS LA NO FL Power GA AL Power S & R National Guard AL SONIC Advancing the Science of Networks in Communities

34 Time Slice 6: 9/3 to 9/4/2005 ARC FEMA Shelter TX MS LA NO FL Outages GA AL Power Urban S & R National Guard AL S & R SONIC Advancing the Science of Networks in Communities

35 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

36 Core Research Socio-technical Drivers for Creating & Sustaining Communities Business Applications PackEdge Community of Practice (P&G) Kraft Design Teams Societal Justice Applications Cultural & Networks Assets In Immigrant Communities (Rockefeller Program on Culture & Creativity) Mapping Digital Media and Learning Networks (MacArthur Foundation) Science Applications CI-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 Entertainment Applications Second Life (NSF, Army Research Institute, Linden Labs) EverQuest II (NSF, Army Research Institute, Linden Labs) SONIC Advancing the Science of Networks in Communities

37 SONIC Advancing the Science of Networks in Communities Online and Offline

38 Four Types of Relations in EQ2 Partnership: Two players play together in combat activities; Instant messaging: Two players exchange messages through Sony universal chat system Player trade: Players meet “face-to-face” in EQ2 and one gives items to another; Mail: One player sends a message and/or items to others by in-game mail SynchronousAsynchronous Interpersonal interactionPartnership, Instant messaging Transactional interactionPlayer tradeMail SONIC Advancing the Science of Networks in Communities

39 Data Description 3140 players from Aug 25 to Aug 31 2006, in Antonia Bayle – 2998 US, 142 CA ; 2447 male, 693 female Demographic information – Gender, age, and account age (years played Sony games) – Zip code, state, and country SONIC Advancing the Science of Networks in Communities

40 Partnership TradeMail Instant messaging Black: male Red: female SONIC Advancing the Science of Networks in Communities

41 Results Selectivity and transitivity (friend of a friend) exists in all online relations. Homophily of age and game experience is supported in all four relations. Distance matters but short distances are more important. Individuals living within 50 Km are 22.6 times more likely to be partners than those who live between 50 and 800 Km. Time zones impacts gaming and trading but not IM and mail. Individuals in the same time zone are 1.25 times more likely to be game partners than the individuals with one hour difference (but no time zone effect for Gender homophily is not supported for all relations and female players are more likely to interact with the male players. SONIC Advancing the Science of Networks in Communities

42 Core Research Socio-technical Drivers for Creating & Sustaining Communities Business Applications PackEdge Community of Practice (P&G) Kraft Design Teams Societal Justice Applications Cultural & Networks Assets In Immigrant Communities (Rockefeller Program on Culture & Creativity) Mapping Digital Media and Learning Networks (MacArthur Foundation) Entertainment Applications Second Life (NSF, Army Research Institute, Linden Labs) EverQuest II (NSF, Army Research Institute, Linden Labs) Science Applications CI-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

43 Friendship in Second Life Teen Grid nTeen Second Life uAn international gathering place for teens 13-17 to make friends and to play, learn and create. nAll active players in the second quarter in 2007 u2,456 users and 21,232 friendship nDo Homophily and Proximity still apply? SONIC Advancing the Science of Networks in Communities

44 Female Male Size indicates age SONIC Advancing the Science of Networks in Communities

45 Hypotheses Tested H1: Friendship ties are not random. H2: Geographic proximity is positively associated with friendship formation. H3: Digital proximity (time spent online) is positively associated with friendship formation. H4: Temporal proximity (joining at similar times) is positively associated with friendship formation. H5: Age homophily are more likely to form friendships (though not very strong) H6: Friendships tend to be balanced (friend of a friend). SONIC Advancing the Science of Networks in Communities

46 Tobacco Research: TobIG Demo Computational Nanotechnology: nanoHUB Demo Cyberinfrastructure: CI-Scope Demo Oncofertility: Onco-IKNOWTobIG DemonanoHUB DemoCI-Scope DemoOnco-IKNOW From Understanding to Enabling Networks in … SONIC Advancing the Science of Networks in Communities

47 Summary n Web Science is well poised to make a quantum intellectual leap by facilitating collaboration that leverages recent advances in: u Theories: Theories about the social motivations for creating, maintaining, dissolving and re-creating links in multidimensional networks u Data: Developments in Semantic Web/Web 2.0 provide the technological capability to capture, store and query relational metadata needed to more effectively understand and enable communities. u Methods: Ensemble of qualitative and quantitative methods (exponential random graph modeling (p*) techniques) enable theoretically grounded network recommendations u Computational infrastructure: Cloud computing and petascale applications are critical to face the computational challenges in analyzing the data SONIC Advancing the Science of Networks in Communities

48 Acknowledgements SONIC Advancing the Science of Networks in Communities

49 SONIC Team Zack Johnson Undergraduate Mengxiao Zhu Jingling Li Jeffrey Treem Doctoral candidate Research Programmer Doctoral candidate York Yao Research Programmer Yun Huang Annie Wang David Huffaker Post-doc Post-doc Doctoral candidate Brian Keegan Doctoral Candidate SONIC Advancing the Science of Networks in Communities

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