Networks for Newbies: A NonTechnical Introduction to Social Network Analysis

1
Networks for Newbies A Non-Technical
Introduction to Social Network Analysis

• Prof. Barry Wellman, INSNA Founder
• Prof. Alexandra Marin
• Department of Sociology
• University of Toronto
• wellman_at_chass.utoronto.ca
• www.chass.utoronto.ca/wellman
• International Sunbelt Social Network
  ConferenceSt Petersburg FL, January 2008

2
Workshop Goals

• Understand what social network analysis is
• Understand how SNA could be useful for your work
• Be aware of the decisions youll need to make to
  use it in your research
• Learn some basic network measures
• Link to and differentiate from
• Social network software, such as MyFace
• Network science
• Learn about resourcs for further info

3
Two Other Ways to Look at Reality

• Individuals as Aggregates of Attributes
• All Possess One or More Properties as an
  Aggregate of Individuals
• Examples Sex, Education, Bank, Rich Countries
• Groups
• (Almost) All Densely-Knit Within Tight Boundary
• Thought of as a Solidary Unit (Really a Special
  Network)
• Family, Workgroup, Community, Association, Soviet
  Bloc

4
What is a Network?

• Network
• Set of Connected Units People, Organizations,
  Networks
• Relations Direct relations or common
  affiliations
• Talking, cheating, working together, trade,
  liking, partnership, citation, disease
  transmission, marriage, travel
• Can Belong to Multiple Networks
• Examples Friendship, Organizational,
  Inter-Organizational, World-System, Internet

5
Nodes, Relationships Ties

• Nodes A Unit That Possibly is Connected
• Individuals, Households, Workgroups,Organizations,
  States
• Relationships (A Specific Type of Connection) A
  Role Relationship
• 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
• One-Mode, Two-Mode Networks

6
What is Social Network Analysis

• The Analysis of Networks! Simple enough, eh?
• But network analysis implies a new perspective
  for understanding social behavior
• Not a method, a cognitive perspective that has
  developed methods for applying that perspective
  to empirical research

7
The Social Network Perspective

• Relations, not attributes
• No independence!
• Dyadic relations operate in the context of
  broader social structures

8
Networks, Not Groups

• Groups are a short-hand for special kinds of
  networks cohesive, densely-knit
  tightly-bounded
• Group binary membership status
• Network varied levels of embeddededness,
  variable knit, often loosely bounded
• Networks can comprehend multiple memberships
  commitments, as well as conflicting interests

9
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
• Emergent Properties (Simmel vs. Homans)

10
Relations, Not Attributes

• Behavior of actors is best explained by
• Position of actors in patterns of relations
• Not the attributes of actors (sex, SES,
  ethnicity)
• Although attributes may be correlated with
  positions
• for example, central high-status white men

11
Dyads are Influenced by Network Context

• 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, British sociologist, anthropologist,
  1970s
• Or, Pattern Quality (Harrison White, late
  1970s)

12
Two Minute History of Sunbelt Conference

• Informal conferences in mid-late 1970s
• Toronto (1974) Hawaii
• Formalized as Sunbelt 1981 annual
• Why Sunbelt?
• Normal Rotation SE US, US West, Europe
• Los Angeles area (2009), Trento, Italia (2010)
  Australia/Japan
• Always Informal, But Serious Work
• This Years Keynote Steve Borgatti
• Former head of INSNA
• Started as a grad student working on UCINet
• Now maintains is a 1-person help desk
• ucinet listserve ucinet_at_yahoogroups.com

13
Source http//nersp.nerdc.ufl.edu/ufruss/contact
me.htm
14
Ten Minute History of INSNA

• Founded by Barry Wellman in 1976-1977
• Sabbatical Travel Carried Tales
• Nick Mullins Every Theory Group Has an
  Organizational Leader
• Owned by Wellman until 1988 as small business
• Bill Richards President, 2003-2007 (died
  suddenly)
• George Barnett VP, became President
• Katie Faust Treasurer Frans Stokman, Euro. Rep.
• Grown from 175 ? 400 ? 1,200 members
• Many More on Listserv (Not Limited to Members)
• Steve Borgatti maintains unmoderated
• Social Networking in Fashion now
• Website www.insna.org -- being upgraded

15
10 Minute Overview - Journals

• Wellman founded,edited,published Connections,
  1977
• Informal journal Useful articles, news,
  gossip, grants, abstracts, book summaries. Will
  be online only, starting in 2008
• George Barnett, Tom Valente edit now
• Lin Freeman founded, edited Social Networks,
  1978-2007. Formal journal Refereed articles.
  Ronald Breiger became co-editor
• Now Patrick Doreian Tom Snijders
• David Krackhardt founded, edits J of Social
  Structure, 2000?
• Online, Refereed
• Lots of visuals
• Articles Appear Occasionally when their time has
  come
• Book Essays Barry Bev Wellman (emeritus)
  Charles Kadushin looking for reviewers

16
10 Minute Overview Key Books

• Elizabeth Bott, Family Social Network, 1957
• J. Clyde Mitchell, Networks, Norms
  Institutions, 1973
• Mark Granovetter, Getting a Job, 1974
• Holland Leinhardt, Perspectives on Social
  Network Research,1979
• S. D. Berkowitz, An Introduction to Structural
  Analysis, 1982
• Knoke Kuklinski, Network Analysis, 1983, Sage,
  low-cost
• Charles Tilly, Big Structures, Large Processes,
  Huge Comparisons, 1984
• Wellman Berkowitz, eds., Social Structures,
  1988
• David Knoke, Political Networks, 1990
• John Scott, Social Network Analysis, 1991
• Ron Burt, Structural Holes, 1992
• Manuel Castells, The Rise of Network Society,
  1996, 2000
• Barry Wellman, Networks in the Global Village,
  1999
• Wasserman Faust, Social Network Analysis, 1992
• Nan Lin, Social Capital (monograph reader),
  2001
• Duncan Watts, Six Degrees, 2003

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10 Minute Overview Software

• UCINet Whole Network Analysis
• Lin Freeman, Steve Borgatti, Martin Everett
• Pajek Vladimir Bagatelj and associates,
  Slovenia
• Sienna Longitudinal network analysis Tom
  Snijders
• MultiNet Whole Network Analysis Bill Richards
• Nodal Characteristics
• NetDraw, plus other visualization programs
• PStar Dyadic Analysis Stan Wasserman
• Structure Ron Burt Not Maintained
• Personal Network Analysis
• SPSS/SAS See Wellman, et al. How To papers
• Egotistics Bernie Hogan, Wojciech Gryz, Barry
  Wellman-beta

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10 Minute Overview Data Basis

• Small Group Sociometry1930s gt (Moreno,
  Bonacich, Cook)
• Finding People Who Enjoy Working Together
• Evolved into Exchange Theory, Small Group Studies
• Ethnographic Studies, 1950s gt (Mitchell, Barnes)
• Does Modernization gt Disconnection?
• Survey Research Personal Networks, 1970s gt
• Community, Support Social Capital, Guanxi
• Mathematics Simulation, 1970s gt (Freeman,
  White)
• Formalist / Methods Substantive Analysis
• Survey Archival Research, Whole Nets, 1970s gt
• Organizational, Inter-Organizational,
  Inter-National Analyses
• Political Structures, 1970s gt (Tilly,
  Wallerstein)
• Social Movements, Mobilization (anti Alienation)
• World Systems (asymmetric structure gt
  Globalization)
• Computer Networks as Social Networks, late 1990s
  gt (Watts)
• Web, Facebook Automated Data Collection. Lots of
  datapoints

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Two Popular New Areas

• Small Worlds and Scale-Free Networks
• Barabasi, Watts
• World Wide Web as Social Networks
• Social Networking Software
• MySpace, Facebook, Hi5, Bebo
• Managing Your Network
• Managing Your Organizations Network
• Interlinking Networks
• Network Aggregation
• Network Science
• Rejects qualitative approachs to network analysis
• Much modelling

20
The Multiple Ways of Network Analysis

• Method The Most Visible Manifestation
• Misleading to Confuse Appearance with Reality
• Data Gathering see previous slide
• Theory Pattern Matters
• Substance
• Community, Organizational, Inter-Organizational,
  Terrorist, World System, Web
• As 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
• Not Actor-Network Theory
• Links to Structural Analyses in Other Disciplines

21
The Social Network Approach

• The world is composed of networks - not
  densely-knit, tightly-bounded groups
• Networks provide flexible means of social
  organization and of thinking about social
  organization
• Networks have emergent properties of structure
  and composition
• Networks are a major source of social capital
  mobilizable in themselves and from their contents
• Networks are self-shaping and reflexive
• Networks scale up to networks of networks

22
How Do Network Analysts Explain Things?

• Some dont. Pure formalists
• How structure affects outcomes
• Structure as providing constraints and
  opportunities
• Structure matters more than individual attributes
• Structure helps explain individual motivations

23
No Explanations, Just Structure

• Structure for the pure joy of Structure
  formalists
• Small-group networks (not popular anymore)
• Small-world networks
• Power-law networks scale free
• How many friends do your friends have?

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Explanation by Structure Alone

• Understanding of motivation not necessary to
  explain outcomes
• Harrison White chains of opportunity (vacancy
  chains)
• Jobs, homes

25
Structure as Constraint Opportunity

• People pursue their golas within structure
• Structure provides opportunities to pursue
  goals constraints on action
• E.g., Ron Burts Structural Holes

26
Structural vs Other Explanations

• Determine how much variation is accounted for by
  structure and how much by other explanations
• E.g., Beverly Wellman Pathways to Back Care
• How people find alternative health care providers

27
Structure as Source of Motivations

• People catch peferences, goals, motivations,
  etc from their networks
• Epidemiology attitudes to birth control AIDs
• Two methods
• Cohesion from those to whey are connected
• E.g., Poison Pills and Golden Parachutes
• Equivalence From those in similar network
  positions
• Citation studies White, Wellman Nazer Matzat

28
Changing Connectivity Groups to Networks

• Densely Knit gt Sparsely-Knit
• Impermeable (Bounded) gt Permeable
• Broadly-Based Solidarity gt Specialized Multiple
  Foci

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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

30
Characteristics of a Networked Society

• Multiplicity of specialized relations
• Management by networks
• More alienation, more maneuverability
• Loosely-coupled organizations / societies
• Less centralized
• The networked society

31
Little Boxes
Glocalization
Networked Individualism
Barry Wellman co-editor Social Structure A
Network ApproachJAI-Elsevier Press 1998
32
Little Boxes ? Ramified Networks

• Each in its Place ? Mobility of People
  and Goods
• United Family ? Serial Marriage, Mixed
  Custody
• Shared Community ? Multiple, Partial
  Personal Nets
• Neighborhoods ? Dispersed Networks
• Voluntary Organizations ? Informal Leisure
• Face-to-Face ? Computer-Mediated
  Communication
• Public Spaces ? Private Spaces
• Focused Work Unit ? Multiple Teams
• Hierarchical Org. ? Networked Organization
• Job in a Company ? Career in a Profession
• Autarky ? Outsourcing
• Office, Factory ? Airplane, Internet,
  Cellphone
• Ascription ? Achievement
• Conglomerates ? Virtual Organizations/Allian
  ces
• Cold War Blocs ? Fluid, Transitory
  Alliances

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Ways of Looking at Networks

• Whole Networks Personal Networks
• Focus on the System or on the Set of Individuals
• Graphs Matrices
• We dream in graphs
• We analyze in matrices

34
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?

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Cumulative GlobeNet Intercitation Through 2000
Howard White Barry Wellman, 2003 Does
Citation Reflect Social Structure
36
Strongest Globenet Co-Citation, Intercitation
Links Thru 2000
37
Duality of Persons Groups

• People Link Groups
• Groups Link People
• An Interpersonal Net is an Interorganizational
  Net
• Ronald Breiger 1973

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The Dualities of Persons and Groups -- Graphs
39
Dualities of Persons and Groups -- Matrices
40
Dualities of Persons and Groups Event-Event
Matrix
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Network Size Matters

• (Robert) Metcalfes Law (Xerox PARC, 1973)
• For every network member added
• The number of possible ties grows by N2
• 10 people gt 102 possible ties 100
• (David) Reeds Law (MIT emeritus, 1997)
• For every network member added
• The number of possible (sub)groups grows by 2N
• 10 people gt 210 possible groups 1,024
• Not only does Reed give a higher number than
  Metcalf
• The disparity increases greatly as N increases
• However, many of these subgroups are very similar

42
Neat Whole Network Methods

• QAP
• Regression of Matrices
• Example Co-Citation (Intellectual Tie)
• Predicts Better than Friendship (Social Tie)
• To Inter-Citation
• Clustering High Density Tight Boundaries
  (Groups)
• Block Modeling
• Similar Role Relationships, Not Necessarily
  Clusters
• Canada Mexico in Same Block US Dominated

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Erickson, 1988 From a Matrix gt . . .
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. . . To a Block Model
45
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

46
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)

47
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

48
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?

49
SNA Branching Out

• Social Movements
• World-Systems Analyses
• Cognitive Networks
• Citation Networks
• Co-Citation
• Inter-Citation
• Applied Networks
• Terrorist Networks
• Corruption Networks
• Web Networks

50
Multilevel AnalysisNew Approach to an Old
Problem

• Switching and Combining Levels
• Individual Agency, Dyadic Dancing, Network
  Facilitation Emergent Properties
• Consider Wider Range of Theories
• Disentangles ( Avoids Nagging Confounding)
• Tie Effects
• Network Effects
• Contingent (Cross-Level) Effects
• Interactions
• Addresses Emergent Properties
• Fundamental Sociological Issue
• Simmel vs. Homans

51
Multilevel Analysis Tie Effects

• Tie Strength Stronger is More Supportive
• Workmates Provide More Everyday Support
• (Multilevel Discovered This)

52
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
• Its Contribution to the Network, Not the Alter

53
Multilevel AnalysisCross-Level, Interaction
Effects

• Kinship
• No longer a solidary system
• Parent-(Adult) Child Interaction
• More Support From Each When gt 1 Parent-Child Tie
• Single P-C Tie 34
• 2 P-C Ties, Probability of Support from Each 54

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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

55
The Internet in Everyday Life

• Computer Networks as Social Networks
• Key Questions
• Community On and Off line
• Networked Life before the Internet
• Netville The Wired Suburb
• Large Web Surveys National Geographic
• Work On and Off line
• Towards Networked Individualism, or
• The Retreat to Little Boxes

56
Social Affordances of New Forms of
Computer-Mediated Connectivity

• Bandwidth
• Ubiquity Anywhere, Anytime
• Convergence Any Media Accesses All
• Portability Especially Wireless
• Globalized Connectivity
• Personalization

57
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 social peripheries
  closer to the center?

58
Research Questions (contd)

• Structure Does the Internet facilitate working
  in loosely-coupled networks rather than dense,
  tight groups?
• Knowledge Management How do people find and
  acquire usable knowledge in networked and virtual
  organizations

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Guiding Research Principles

• Substitute systematic data analysis for hype
• Do field studies, not lab experiments
• Combine statistical with observational info.
• Study the use of each media in larger context
• Work with other disciplines
• Analyze Existing Uses
• Develop New Uses

60
Studies of Community On 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

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Source Dan Heap Parliamentary Campaign 1992 (NDP)
Toronto in the Continental Division of Labor
62
Physical Place and Cyber Place

• Door to Door, Place to Place,
• Person to Person, Role to Role
• Barry Wellman, Changing Connectivity A Future
  History of Y2.03K. Sociological Research Online
  4, 4, February 2000 http//www.socresonline.org.u
  k/4/wellman.html
• Barry Wellman, Physical Place and Cyber Place
  The Rise of Networked Individualism.
  International Journal of Urban and Regional
  Research 25 (2001) June.

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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

64
Place To Place

• (Phones, Networked PCs, Airplanes, Expressways,
  RR, Transit)
• Home, Office Important Contexts,
• Not Intervening Space
• 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

65
Person To Person

• (Cell Phones, Wireless Computing)
• 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

66
Role To Role

• Tailored Communication Media
• Little Awareness of Whole Person
• Portfolios of Specialized Relationships
• Boutiques, not Variety Stores
• Cycling among Specialized
• Communities / Work Groups
• Role-Based Media Interactions
• Management by Network

67
Netville The Wired Suburb

• 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 2 Years
• Survey Research
• Wants, Networks, Activities

68
The entrance to Netville
69
View of Netville
70
Wired and Non-Wired Neighboring in Netville
 
71
Neighboring Ties

• Wired Residents
• Recognize More
• Talk with More
• Invite More Into their Homes
• And are Invited by Them
• Neighbor in a Wider Area

72
Long-Distance Ties (gt50 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

73
Long-Distance Ties

• Wired Residents Say the Internet
• Makes it Easier to Communicate
• Fosters Greater Volume of Communication
• Introduces New Modes of Communication
• Acquire More Diverse Knowledge

74
Netville The Wired Suburb

• With Keith Hampton (MIT)
• Netville Online and Offline Observing and
  Surveying a Wired Suburb. American Behavioral
  Scientist 43, 3 (Nov 1999) 475-92.
• Examining Community in the Digital Neighborhood
  Pp. 475-92 in Digital Cities Technologies,
  Experiences and Future Perspectives, edited by
  Toru Ishida and Katherine Isbister. Berlin
  Springer-Verlag, 2000.
• Long Distance Community in the Network Society
  American Behavioral Scientist, 45 (Nov 2001)
  477-97
• How the Internet Builds Local Community. City
  and Community, 2001

75
National Geographic Survey 2000 and Survey 2001

• Survey 2000 -- Fall 1998
• 35,000 Americans
• 5,000 Canadians
• 15,000 Others
• Survey 2001 -- Fall 2001, N gt 6,000

76
Survey 2000 Research Questions

• Are There Systematic Social Variations in Who
  Uses the Internet for What?
• Does the Internet Multiply, Add To, or Decrease
  Interpersonal Ties?
• Does the Internet Multiply, Add To, or Decrease
  Organizational Involvement?
• Does the Internet Increase, Decrease or Transform
  Community Commitment?
• Does the Internet Increase Knowledge?
• Are There Variations by National Context?

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Computer Supported Cooperative Work

• Fishbowls and Switchboards
• Media Use and Choice
• Cerise
• Indigo
• Networked Scholarly Organizations
• Technet
• Globenet
• Teleworking The Home-Work Nexus

82
The Fishbowl Group Office
Door-to-Door

• All Work Together in Same Room
• All Visible to Each Another
• All have Physical Access to Each Other
• All can see when a Person is Interruptible
• All can see when One Person is with Another
• No Real Secrets
• No Secret Meetings
• Anyone can Observe Conversations Decide to Join
• Little Alert to Others Approaching

83

• Neighbors have Hi Visual Aural Awareness
• Limited Number of Participants
• Densely-Knit (most directly connected)
• Tightly Bounded (most interactions within group)
• Frequent Contact
• Recurrent Interactions
• Long-Duration Ties
• Cooperate for Clear, Collective purposes
• Sense of Group Solidarity (name, collective
  identity)
• Social Control by Supervisor Group

84
The Switchboard Network OfficePerson-to-Person

• Each Works Separately
• Office Doors Closable for Privacy
• Glass in Doors Indicate Interruptibility
• If Doors Locked, Must Knock
• If Doors Open, Request Admission
• Difficult to learn if Person is Dealing with
  Others Unless Door is Open
• Large Number of Potential Interactors
• Average Person knows gt 1,000
• Strangers Friends of Friends May also be
  Contacted

85

• Sparsely-Knit
• Most Dont Know Each Other
• Or Not Aware of Mutual Contact
• No Detailed Knowledge of Indirect Ties
• Loosely-Bounded
• Many Different People Contacted
• Many Different Workplaces
• Can Link with Outside Organizations
• Each Functions Individually
• Collective Activities Transient, Shifting Sets
• Subgroups, Cleavages, Secrets Can Develop

86
Cerise / Indigo CSCW

• Using Video/ Email at Work
• RD Work
• Faculty, Students, Programmers, Admin.
• Caroline Haythornthwaite Laura Garton
• Collaborators
• Survey and Ethnography

87
CSCW Research Questions

• How do Work, Social Roles Affect Media Use?
• Is Email Used Only for Specialized Communication?
• Does Email Use
• Replace, Add To, or Increase F2F, Phone
  Contact?
• Does Email Move Spatial/Social Peripheries
  Socially Closer?
• Does Email Foster Networked Organization?

88
Separate Information Exchange Roles Derived from
Factor Analysis of Specific Exchanges

• Work
• Giving Work
• Receiving Work
• Collaborative Writing
• Computer Programming
• Social
• Sociability
• Major Emotional Support

89
Communication Roles

• Scheduled Meetings
• Classes, Research Meetings
• Email
• Unscheduled Meetings
• Less Frequent, More Wide-Ranging
• Media that Afford Control of Interactions
• Media associated with Group Norms

90
Social Roles

• Sociability, major emotional support
• Media Use follows Pairs Interaction Patterns
• Unscheduled Meetings for Close Friends
• Unscheduled, Scheduled, Email for Work-Only
• Media that Affords Spontaneity
• Social Messages Tag on Work Messages
• Work-Only Pairs Formal Work-Role Pairs

91
The Average Pair

• Specialized
• Exchanges 3/6 Types of Information
• Via 1 or 2 Media
• Unscheduled F2F, Scheduled F2F Meetings, or Email
• Mean 5.2 Information-Media Links / Pair

92
Conclusions The Cerise Study

• Away from Individual Choice, Congruency
• Social Affordances Only Create Possibilities
• Email Used for All Roles
• Work, Knowledge, Sociability and Support
• Email Lowers Status Distances
• Email Network Not a Unique Social Network
• Intermixed with Face-to-Face (low use of phone,
  video, fax)
• Reduces Temporal as well as Spatial Distances

93

• The More Email, the More F2F Contact
• The More Intense Work Friendship Tie
• The More Frequent Email
• Independent Predictors Friendship a bit Stronger
• The More Intense Work Friendship Tie
• The More Types of Media Used to Communicate
• Independent Predictors Friendship Stronger
• F2F the Medium of choice in weaker ties.
• In Stronger Ties, Email Supplements F2F

94
Indigo Work Interaction Time 1
Work Interaction (All Media) Prior to Telepresence
95
Indigo Work Interaction Time 3
Work Interaction (All Media) 14 months after
Telepresence Intro Greater Decentralization
96
Cerise / Indigo Papers

• Caroline Haythornthwaite and Barry Wellman,
  Work, Friendship and Media Use for Information
  Exchange in a Networked Organization.Journal of
  the American Society for Information Science 49
  (1998) 1101-14
• Marilyn Mantei, Ronald Baecker, William Buxton,
  Thomas Milligan, Abigail Sellen and Barry
  Wellman. "Experiences in the Use of a Media
  Space." 1992. Pp 372-78 in Groupware, edited by
  David Marca and Geoffrey Bock. Los Alamitos, CA
  IEEE Computer Society Press, 1992.
• Caroline Haythornthwaite, Barry Wellman Marilyn
  Mantei Work Relationships and Media Use. Group
  Decision and Negotiation 4 (1995) 193-211.
• Caroline Haythornthwaite, Barry Wellman Laura
  Garton, Work and Community Via Computer-Mediated
  Communication. Pp. 199-226 in Psychology and the
  Internet, edited by Jayne Gackenbach. San Diego
  Academic Press, 1998.

97
Netting Scholars Communities of Practice
Inquiry

• Emmanuel Koku, Nancy Nazer Barry Wellman
• Netting Scholars Online and Offline.
• American Behavioral Scientist, 44 ,10 (June,
  2001) 1750-72
• Emmanuel Koku Barry Wellman
• Scholarly Networks as Learning Communities
• In Designing Virtual Communities in the Service
  of Learning, Edited by Sasha Barab Rob
  Kling. Cambridge Cambridge University Press,
  2002

98
Comparison of 2 Scholarly Networks
99

• Globenet members use both F2F email to get
  their joint projects done. The dispersion of
  members across Canada, U.S. U.K. leads them to
  use email as a collaborative tool.

100

• .
• For Globenetters, the distance between members of
  scholarly pairs is unrelated to the frequency of
  their email contact.
• Except when theyre in the same building

101

• Friendship is the strongest predictor to
  face-to-face email contact in Technet Globenet

102

• The scholarly relationship of collaborating on a
  project is the second strongest predictor of
  frequent F2F contact frequent email contact.
• It friendship are the only 2 significant
  predictors.

103

• Congruent with the theories of media use Tasks
  requiring complex negotiations preferably
  conducted via richer F2F contacts.
• Technet members use F2F contact when possible.
• Email fills in temporal informational gaps.
  Those Technet members who often read each others
  work, communicate more by email.

104

• Where F2F contact is easily done, it is the
  preferred medium for collaborative work.
• However, colleagues easily share their ideas and
  their work or announce its existence by email
  and web postings.
• They do not have to walk over to each others
  offices to do this, although Canadian winters can
  inhibit in-person visits

105
Sources of Prominence in Globenet

• External Sources Important for Gaining Entrance
• Scholarly Status
• Niche
• Plus Perceived Internal Congeniality
• Internal Sources Important Within Network
• Knights of the Roundtable
• Formal Role
• Scholarly Communication within Network
• Number of Friendships

106
Summary Ties

• Internet Supports Strong Weak Ties
• Evidence Netville, Netting Scholars, Cerise,
  Telework
• Internet Supports Instrumental Socioemotional
  Ties
• Evidence Netville, National Geographic, Netting
  Scholars, Cerise, Telework
• Ties Rarely are Internet-Only
• Evidence Netville, National Geographic, Netting
  Scholars, Cerise, Telework
• Internet Replaces Fax May Reduce Phone
• Not F2F
• Evidence Netville, Netting Scholars, Cerise

107
Summary Local Social Capital

• Multiplied Number Range of Neighbors
• Evidence Netville
• Increased Contact with Existing Neighbors
  Email Adds On to Same Levels of F2F, Phone
• Evidence National Geographic, Berkeley,
  Netville?
• Demand for Local Information
• Evidence Netville, Berkeley, Small City Study

108
Summary Long Distance Ties

• Increased Contact with Long Distance Ties
  Email Adds On to Same Levels of F2F, Phone1.
  Friends More than Kin2. Long-Distance Ties More
  than Local3. Post Used Only for Rituals
  (Birthdays, Christmas)
• Evidence National Geographic, Netville

109
Summary Long Distance Ties

• Increased Contact with Long Distance Ties
  Email Adds On to Same Levels of F2F, Phone1.
  Friends More than Kin2. Long-Distance Ties More
  than Local3. Post Used Only for Rituals
  (Birthdays, Christmas)
• Evidence National Geographic, Netville

110
SummaryComputer-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

111
Summary The GloCalization Paradox

• Surf and Email Globally
• Stay Wired at Office/Home to be Online
• Desire for Local/Distant Services and Information
  
• Internet Supplements/Augments F2F
• Doesnt Replace It
• Rarely Used Exclusively
• Media Choice? By Any Means Available
• Many Emails are Local Within the Workgroup
  or Community
• Local Becomes Just Another Interest
• Evidence Netville, National Geographic, Small
  Cities, Berkeley, Netting Scholars, Cerise,
  Indigo, Telework

112
Summary Social Network Structure

• Internet Aids Both Direct Indirect Connections
• Knowledge Acquisition Management
• Accessing Friends of Friends
• Forwarding Folding In Making Indirect Ties
  Direct Ties
• Social and Spatial Peripheries Closer to the
  Center
• Shift from Spatial Propinquity to Shared
  Interests
• Shifting, Fluid Structures
• Networked, Long-Distance Coordination Reports

113
Conclusions Changing Connectivity

• By Any Means Available
• Door-to-Door gt Place-to-Place gt
  Person-to-Person Connectivity
• Less Solidary Households
• Dual Careers
• Multiple Schedules
• Multiple Marriages
• New Forms of Community
• Partial Membership in Multiple Communities
• Networked Virtual Work Relationships

114
ConclusionsRole-to-Role Relationships

• Partial Communities of Shared, Specialized
  Interest
• Importance of Informal Network Capital
• Production
• Reproduction
• Externalities
• Bridging and Bonding Ties

115
ConclusionsHow a Network Society Looks

• Multiplicity of Specialized Relations
• Management by Networks
• More Uncertainty, More Maneuverability
• Boutiques, not General Stores
• Less Palpable than Traditional Solidarities
• Need Navigation Tools
• An Electronic Group is Virtually a Social
  Network." Pp. 179-205 in Culture of the Internet,
  edited by Sara Kiesler. Mahwah, NJ Lawrence
  Erlbaum, 1997.

116
Conclusions Shift to New Kinds Of Community
Workgroups

• Partial Membership in Multiple Networks
• Multiple Reports
• Long-Distance Relationships
• Transitory Work Relationships
• Each Person Operates Own Network
• Online Interactions Linked with Offline
• Status, Power, Social Characteristics Important
• Sparsely-Knit Fewer Direct Connections Than
  Door-To-Door -- Need for Institutional Memory
  Knowledge Management
• IKNOW (Nosh Contractor) Network Tracer
• ContactMap (Bonnie Nardi Steve Whittaker)
  Network Accumulator

117
Conclusions The Rise of Personalized Networking

• Individual Agency Constrained by Nets
• Personalization rather than Group Behavior
• Interpersonal Ties Dancing Dyadic Duets
• Bandwidth
• Sparsely-Knit, Physically-Dispersed Ties
• Social Networks
• Multiple, Ad Hoc
• Wireless Portability

118
Design Considerations for a Networked Society
Connecting

• Open List
• Indicate Presence, Awareness, Availability
• Prioritize from Deductive, Inductive Ad Hoc
  Data
• Prioritize by Locale
• Searchable and Sortable List
• By a Variety of Attributes

119
Design Considerations for a Networked Society
Autonomy

• Incorporate Third Parties
• Quickly Set Up Dissolve Work Teams
• Privacy Protection
• Control Who is Aware of the Interaction
• Alert if Others Lurking
• File Access
• Cross-Platform Communication

120
Three Modes of Interaction Social Structure
121
Boundaries
122
Boundaries (continued)
123
Interpersonal Interactions
124
Social Networks
125
Norms and Perceptions
126
After 9-11 Retreat to Little Boxes?

• Back from Networks to Little Boxes?
• Re-establishing Tight Boundaries
• Knowledge Workers Spatial Mobility Hindered
• Goods Made and Sold Locally
• Distrust of Outsiders
• Drawing into Densely-Knit Groups
• Gated Communities
• Gated Work All Work Done on Premises Autarky
• Direct Ties, F2F Ties Replace
• Indirect, Computer Mediated Ties
• Network Analysis Used by Terrorists Governments

127
Little Boxes ? Ramified Networks

• Each in its Place ? Mobility of People and
  Goods
• United Family ? Serial Marriage, Mixed Custody
• Shared Community ? Multiple, Partial Personal
  Nets
• Neighborhoods ? Dispersed Networks
• Voluntary Organizations ? Informal Leisure
• Face-to-Face ? Computer-Mediated
  Communication
• Public Spaces ? Private Spaces
• Focused Work Unit ? Networked Organizations
• Job in a Company ? Career in a Profession
• Autarky ? Outsourcing
• Office, Factory ? Airplane, Internet,
  Cellphone
• Ascription ? Achievement
• Hierarchies ? Matrix Management
• Conglomerates ? Virtual Organizations/Alliances
  
• Cold War Blocs ? Fluid, Transitory Alliances

128
Edited Books

• The Internet in Everyday Life
• Caroline Haythornthwaite, co-editor
• Oxford Blackwell Publishers 2002
• Preliminary American Behavioral Scientist, Nov
  2001
• Networks in the Global Village
• Boulder, CO Westview Press 1999
• Social Structures A Network Approach
• S. D. Berkowitz, co-editor
• Cambridge University Press, 1988
• Reprinted Elsevier-JAI Press, 1997
• Reprinted CSPI Press, Toronto, 2003

129
Recent Integrative Articles

• Computer Networks as Social Networks Science
  293 (Sept 14, 2001) 2031-34.
• Designing the Internet for a Networked Society.
• Communications of the ACM, April 2002 in
  press.
• Research Supported By
• Institute of Knowledge Management,
• CITO, Mitel, National Science Foundation (US),
• Social Science Humanities Research Council of
  Canada

130
Thank You -- Barry Wellman
Networks For Ex-Newbies

• Director, NetLabCentre for Urban
  Community StudiesUniversity of TorontoToronto,
  Canada M5S 1A1wellman_at_chass.utoronto.cawww.chass
  .utoronto.ca/wellman