Barry Wellman

1. Computer Networks are Social Networks Barry Wellman NetLab Director Centre for Urban & Community Studies University of Toronto Toronto, Canada M5S 1A1 wellman@chass.utoronto.cawww.chass.utoronto.ca/~wellman

2. NetLab

3. Three Ways to Look at Reality • Categories • All Possess One or More Properties as an Aggregate of Individuals • Examples: Men, Developed Countries • Groups • (Almost) All Densely-Knit Within Tight Boundary • Thought of as a Solidary Unit (Really a Special Network) • Family, Workgroup, Community • Networks • Set of Connected Units: People, Organizations, Networks • Can Belong to Multiple Network • Examples: Friendship, Organizational, Inter-Organizational, World-System, Internet

4. In a Sentence – “To Discover How A, Who is in Touch with B and C, Is Affected by the Relation Between B & C” John Barnes

5. A Network is More Than The Sum of Its Ties • A Network Consists of One or More Nodes • Could be Persons, Organizations, Groups, Nations • Connected by One or More Ties • Could be One or More Relationships • That Form Distinct, Analyzable Patterns • Can Study Patterns of Relationships OR Ties

6. The Multiple Ways of Network Analysis • Method – The Most Visible Manifestation • Misleading to Confuse Appearance with Reality • Theory – Pattern Matters • Substance • Community, Organizational, Inter-Organizational, Terrorist, World System • An Add-On: • Add a Few Network Measures to a Study • Integrated Approach • A Way of Looking at the World: • Theory, Data Collection, Data Analysis, Substantive Analysis

7. The Social Network Approach • Networks provide flexible means of social organization and of thinking about social organization • The world is composed of networks - not densely-knit, tightly-bounded groups • Networks are a major source of social capital mobilizable in themselves and from their contents • Moving from a hierarchical society bound up in little boxes to a network – and networking – society • Networks have emergent properties of structure and composition

8. The Social Network Approach • Networks are self-shaping and reflexive • Networks scale up to networks of networks • Multiple communities / work networks • Multiplicity of specialized relations • Management by networks • More alienation, more maneuverability • Loosely-coupled organizations / societies • Less centralized • The networked society

9. Relationships & Ties Distinguish Between: • Relationships (One Type of Relation) • Gives Emotional Support • Sends Money To • Attacks • Ties (One or More Relationships) • Friendship (with possibly many relationships) • Affiliations (Person – Organization) • Works for IBM; INSNA Member; Football Team

10. Groups GloCalization Networked Individualism

11. Groups to Networks: • Changing Connectivity • Sparsely-Knit • Loosely-Bounded • Multiple Foci • Two Ways of Looking • Whole Networks • Personal Networks

12. Themes of Social Network Analysis • Ethnographic Studies • Does Modernization > Disconnection? • Small Group “Sociometry” • Finding People Who Enjoy Working Together • Survey Research: Personal Networks • Community, Support & Social Capital, “Guanxi” • Internet • Archival Research • Inter-Organizational, Inter-National Analyses

13. Social Network Analysis: More Flavors • Diffusion of Information (& Viruses) • Flows Through Systems • Organizational Analyses • “Real” Organization” • Knowledge Acquisition & Management • Inter-Organizational Analysis • Is There a Ruling Elite • Strategies, Deals • Networking: How People Network • As a Strategy • Unconscious Behavior • Are There Networking Personality Types?

14. Social Network Analysis: Branching Out • Social Movements • World-Systems Analyses • Cognitive Networks • Citation Networks • Co-Citation • Inter-Citation • Applied Networks • Terrorist Networks • Corruption Networks • Discovered by Physicists

15. Networked Individualism • Moving from a society bound up in little boxes to a multiple network – and networking – society • Networks are a flexible means of social organization • Networks are a major source of social capital: mobilizable in themselves & from their contents • Networks link: • Persons • Within organizations • Between organizations and institutions

16. Whole Social Networks • Comprehensive Set of Role Relationships in an Entire Social System • Analyze Each Role Relationship – Can Combine • Composition: % Women; Heterogeneity; % Weak Ties • Structure: Pattern of Ties • Village, Organization, Kinship, Enclaves, World-System • Copernican Airplane View • Typical Methods: Cliques, Blocks, Centrality, Flows • Examples: (1)What is the Real Structure of an Organization? • (2) How Does Information Flow Through a Village?

17. Costs of Whole Network Analysis • Requires a Roster of Entire Population • Requires (Imposition of) a Social Boundary • This May Assume What You Want to Find • Hard to Handle Missing Data • Needs Special Analytic Packages • Becoming Easier to Use

18. Personal Social Networks • Ptolemaic Ego-Centered View • Good for Unbounded Networks • Often Uses Survey Research • Example: (1)Do Densely-Knit Networks Provide More Support? (structure) • (2) Do More Central People Get More Support? (network) • (2) Do Women Provide More Support? (composition) • (3) Do Face-to-Face Ties Provide More Support Than Internet Ties? (relational) • (4) Are People More Isolated Now? (ego)

19. Costs of Personal Network Studies • Concentrates on Strong Ties • Collecting Proper Data in Survey Takes Much Time • Ignores Ecological Juxtapositions • Hard to Aggregate from Personal Network to Whole Network • Easier to Decompose Whole Network • (Haythornthwaite & Wellman) • Often Relies on Respondents’ Reports

20. Duality of Persons & Groups • People Link Groups • Groups Link People • Breiger 1973

21. “Network of Networks” An Interpersonal Network as An Interorganizational Network Barry Wellman

22. Multilevel Analysis – Tie Effects • Tie Strength: Stronger is More Supportive • Workmates: Provide More Everyday Support • (Multilevel Discovered This)

23. Multilevel Analysis– Network Effects • Network Size • Not Only More Support from Entire Network • More Probability of Support from Each Network Member • Mutual Ties (Reciprocity): • Those Who Have More Ties with Network Members Provide More Support • Cross-Level Effect Stronger (and Attenuates) Dyadic (Tie-Level) Effect It’s Contribution to the Network, Not the Alter

24. Multilevel Analysis:Cross-Level, Interaction Effects • Kinship • No longer a solidary system • Parent-(Adult) Child Interaction • More Support From Each When > 1 Parent-Child Tie • Single P-C Tie: 34% • 2+ P-C Ties, Probability of Support from Each: 54%

25. Multilevel Interactions-- Accessibility • 37% of Moderately Accessible Ties Provide Everyday Support • But If Overall Network Is Moderately Supportive, • 54% of All Network Members Provide Everyday Support • Women More Supportive In Nets with More Women

26. The Internet in Everyday Life • Computer Networks as Social Networks • Key Questions • Community Networks On and Off line • Networked Life before the Internet • Netville: The Wired Suburb • Large Web Surveys: National Geographic • Work On and Off line • Which Media for What Purpose? • Communities of Practice • Teleworking • Towards Networked Individualism, or The Retreat to Little Boxes

27. Overarching Questions • How is the Internet Being Incorporated Into Everyday Life • Does the Internet Multiply, Decrease, Add To • Other Forms of Communication • Overall Communication • How is the Structure of Interpersonal Relations Affected • How Does Everyday Life Affect the Internet

28. What is Community? • At Work, in the Neighborhood, Long-Distance, On the Internet • 59 Definitions (see my Law Commission report) • Interpersonal Ties That Provide: • Sociability • Support • Information • Sense of Belonging

29. Stretching the Community Concept • Shared Categories • “The Jewish Community” • Shared Ecologies / Spaces • Real – Apartment Building • Virtual – e-Opinion, e-Bay • Conflict • Communal Strife (“Fast Runner”) • Gamers (cooperation and conflict) • Instrumental • Co-Workers (vs Communities of Practice)

30. What’s Driving Changes? • Transportation & Communication Have Become Individualized • Dual Careers – Multiple Schedules • Multiple Employers • Sequential and Contemporaneous • Separation of Work and Home as Physical Places • Movement of Work away from Workplace: • Teleworker, Flex Worker, Road Warrior • Computerization Allows Personalization • No Over-Arching Social Controllers

31. Groups Networks ** Each in its PlaceMobility of People and Goods ** • United Family  Serial Marriage, Mixed Custody • Shared Community  Multiple & Partial Personal Nets • Neighborhoods  Dispersed Communities • Surveillance  Privacy • Control  Autonomy • Voluntary Organizations  Informal Leisure • Face-to-Face Computer-Mediated Communication • Public Spaces  Private Spaces • Visibility  Anonymity • Focused Work Unit  Networked Organization • Job in a Company  Career in a Profession • Autarky  Outsourcing • Office, Factory  Airplane, Internet, Cellphone • Ascription  Achievement • Hierarchies  Multiple Reporting Relationships • Conglomerates  Virtual Organizations/Alliances • Collective Security  Civil Liberties • Cold War Blocs  Fluid, Transitory Alliances

32. Door To Door • Old Workgroups/ Communities Based on Propinquity, Kinship • Pre-Industrial Villages, Wandering Bands • All Observe and Interact with All • Deal with Only One Group • Knowledge Comes Only From Within the Group – and Stays Within the Group

33. Place To Place (Phones, Networked PCs, Airplanes, Expressways, RR, Transit) Home, Office Important Contexts, • Not Intervening Space • Specialized Relationships – Not MultiStranded Ties • Ramified & Sparsely Knit: Not Local Solidarities • Not neighborhood-based • Not densely-knit with a group feeling • Partial Membership in Multiple Workgroups/ Communities • Often Based on Shared Interest • Connectivity Beyond Neighborhood, Work Site • Household to Household / Work Group to Work Group • Domestication, Feminization of Community • Deal with Multiple Groups • Knowledge Comes From Internal & External Sources • “GloCalization”: Globally Connected, Locally Invested

34. Person To Person (Mobile Phones, Wireless Computing, Segway) Little Awareness of Context • Individual, Not Household or Work Group • Personalized Networking • Tailored Media Interactions • Private Desires Replace Public Civility • Less Caring for Strangers, Fewer Weak Ties • Online Interactions Linked with Offline • Dissolution of the Internal: All Knowledge is External • Broader Social Context Necessary • But Often Taken for Granted

35. Analyzing the Internet: Three Fallacies • Presentistism • Assumes that only phenomena that happened since the Net are relevant to understanding the Net • Parochialism • Assumes that only phenomena that happen on the Net are relevant to understanding the Net • Punditism • Makes “common sense” pronouncements instead of investigating systematic research

36. Myopic to Look at the Internet As a Special World • Computers are NOT the Mothers of All Invention • Net’s Demographics Approaching Population’s • Gender, Income, Education, Ethnicity, Age • People Rapidly Become Experienced • Users Become Frequent Users • The Real Digital Divide is Know-How, Not Access

37. Social Affordances of New Forms of Computer-Mediated Connectivity • Bandwidth • Ubiquity – Anywhere, Anytime • Convergence – Any Media Accesses All • Portability – Especially Wireless • Globalized Connectivity • Personalization

38. Research Questions • Ties: Does the Internet support all types of ties? • Weak and Strong? • Instrumental and Socio-Emotional? • Online-Only or Using Internet & Other Media (F2F, Phone)? • Social Capital: Has the Internet increased,decreased, or multiplied contact – at work, in society? • Interpersonally – Locally • Interpersonally – Long Distance • Organizationally • GloCalization:Has the map of the world dissolved so much that distance does not matter? Has the Internet brought spatial and socialperipheries closer to the center?

39. Does the Internet Add To Social Capital • Internet Integrates into Everyday Life • Email, IM, Phone, F2F Mutually Reinforcing • Whichever is Handy & Appropriate • More Useful for Existing Ties than New Ones

40. Does the Internet Decrease Social Capital • Difficulty in Using > Alienation & Depression • Failure to Live Up to Hype • Time-Sink • Diverts from “Real” Household, Community, Work Relations • Weak Ties Crowd Out Strong Ties

41. Does the Internet Add To Social Capital • Internet Integrates into Everyday Life • Email, IM, Phone, F2F Mutually Reinforcing • Whichever is Handy & Appropriate • More Useful for Existing Ties than New Ones

42. Other NetLab Research Questions Structure: Does the Internet facilitate working in loosely-couplednetworks rather than dense, tight groups? Knowledge Management: How do people find and acquire usable knowledge in networked and virtual organizations

43. The Internet in Everyday Life • Barry Wellman & Caroline Haythornthwaite, eds. • Blackwells, Fall 2002 • Authors Include: Matei & Ball-Rokeach; Katz & Rice; • Castells; Rheingold; Anderson & Tracey; • Kazmer & Haythornthwaite; Kavanaugh & Patterson; • Phil Howard, Raine & S Jones; Miyata; • Lunn & Suman; Wagner, Pischner, Haisken-DeWitt • 3 NetLab research articles (+ intro essay) • Hampton & Wellman, Long-Distance Ties • Quan-Haase & Wellman, Social Capital On and Offline • Chen, Boase & Wellman, Uses & Users Around the World

44. NetLab’s Studies of Community On- Line and Off-Line Pre-Internet Networked Communities “Netville”: The Wired Suburb National Geographic Web Survey 1998, 2001 Other Internet Community Studies Barry Wellman,“The Network Community” Introduction to Networks in the Global Village Westview Press, 1999

45. Source: Dan Heap Parliamentary Campaign 1992 (NDP) Toronto in the Continental Division of Labor

46. “Netville”: The Wired Suburb(with Keith Hampton, MIT) Leading-Edge Development Exurban Toronto • Mid-Priced, Detached Tract Homes • Bell Canada, etc. Field Trial • 10Mb/sec, ATM-Based, No-Cost Internet Services • Ethnographic Fieldwork • Hampton Lived There for Nearly 2 Years • Survey Research • Wants, Networks, Activities

47. View ofNetville

48. Mean Number of Neighbors: Wired (37) Non-Wired (20) Wired/NonWired Ratio Signif. Level (p <) Recognized by Name 25.5 8.4 3.0 .00 Talk with Regularly 6.3 3.1 2.0 .06 Invited into Own Home 3.9 2.7 1.4 .14 Invited into Neighbors’ Homes 3.9 2.5 1.6 .14 # of Intervening Lots to Known Neighbors 7.5 5.6 1.4 .08 “Wired” and “Non-Wired” Neighboring in Netville

49. Computer-Mediated Communication • Not only supports online “virtual” communities • Supports and maintains existing ties: strong & weak • Increases connectivity with weak ties • Supports both local and non-local social ties • In Neighborhood, High-speed Network: • Increases local network size • Increases amount of local contact • Long-Distance, High-Speed Network • Increases amount of contact • Increases support exchanged • Facilitates contact with geographical periphery

50. Long-Distance Ties(>50 km/30 mi ) Compared to One Year before Moving to Netville, Wired Residents Have More Than Non-Wired: • Social Contact – especially over 500 km • Help Given (e.g., childcare, home repair) • Help Received from Friends and Relatives • Especially between 50 and 500 km • See“Long Distance Community in the Network Society” American Behavioral Scientist, 45 (Nov 2001): 477-97; Revised version in The Internet in Everyday Life (2002)