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Networks for Newbies: A NonTechnical Introduction to Social Network Analysis


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Title: Networks for Newbies: A NonTechnical Introduction to Social Network Analysis

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
  • International Sunbelt Social Network
    ConferenceSt Petersburg FL, January 2008

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

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
  • Family, Workgroup, Community, Association, Soviet

What is a Network?
  • Network
  • Set of Connected Units People, Organizations,
  • Relations Direct relations or common
  • 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

Nodes, Relationships Ties
  • Nodes A Unit That Possibly is Connected
  • Individuals, Households, Workgroups,Organizations,
  • 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

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

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

Networks, Not Groups
  • Groups are a short-hand for special kinds of
    networks cohesive, densely-knit
  • 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

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)

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

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,
  • Or, Pattern Quality (Harrison White, late

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)
  • 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

Source http//
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
  • 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 -- being upgraded

10 Minute Overview - Journals
  • Wellman founded,edited,published Connections,
  • 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
  • Book Essays Barry Bev Wellman (emeritus)
    Charles Kadushin looking for reviewers

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,
  • Charles Tilly, Big Structures, Large Processes,
    Huge Comparisons, 1984
  • Wellman Berkowitz, eds., Social Structures,
  • 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,
  • Wasserman Faust, Social Network Analysis, 1992
  • Nan Lin, Social Capital (monograph reader),
  • Duncan Watts, Six Degrees, 2003

10 Minute Overview Software
  • UCINet Whole Network Analysis
  • Lin Freeman, Steve Borgatti, Martin Everett
  • Pajek Vladimir Bagatelj and associates,
  • Sienna Longitudinal network analysis Tom
  • 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

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,
  • Formalist / Methods Substantive Analysis
  • Survey Archival Research, Whole Nets, 1970s gt
  • Organizational, Inter-Organizational,
    Inter-National Analyses
  • Political Structures, 1970s gt (Tilly,
  • Social Movements, Mobilization (anti Alienation)
  • World Systems (asymmetric structure gt
  • Computer Networks as Social Networks, late 1990s
    gt (Watts)
  • Web, Facebook Automated Data Collection. Lots of

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

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

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
  • 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

How Do Network Analysts Explain Things?
  • Some dont. Pure formalists
  • How structure affects outcomes
  • Structure as providing constraints and
  • Structure matters more than individual attributes
  • Structure helps explain individual motivations

No Explanations, Just Structure
  • Structure for the pure joy of Structure
  • Small-group networks (not popular anymore)
  • Small-world networks
  • Power-law networks scale free
  • How many friends do your friends have?

Explanation by Structure Alone
  • Understanding of motivation not necessary to
    explain outcomes
  • Harrison White chains of opportunity (vacancy
  • Jobs, homes

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

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

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
  • Citation studies White, Wellman Nazer Matzat

Changing Connectivity Groups to Networks
  • Densely Knit gt Sparsely-Knit
  • Impermeable (Bounded) gt Permeable
  • Broadly-Based Solidarity gt Specialized Multiple

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
  • Networks are a major source of social capital
    mobilizable in themselves from their contents
  • Networks link
  • Persons
  • Within organizations
  • Between organizations and institutions

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

Little Boxes
Networked Individualism
Barry Wellman co-editor Social Structure A
Network ApproachJAI-Elsevier Press 1998
Little Boxes ? Ramified Networks
  • Each in its Place ? Mobility of People
    and Goods
  • United Family ? Serial Marriage, Mixed
  • Shared Community ? Multiple, Partial
    Personal Nets
  • Neighborhoods ? Dispersed Networks
  • Voluntary Organizations ? Informal Leisure
  • Face-to-Face ? Computer-Mediated
  • 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,
  • Ascription ? Achievement
  • Conglomerates ? Virtual Organizations/Allian
  • Cold War Blocs ? Fluid, Transitory

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

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,
  • Copernican Airplane View
  • Typical Methods Cliques, Blocks, Centrality,
  • Examples (1) What is the Real Structure of an
  • (2) How Does Information Flow Through a Village?

Cumulative GlobeNet Intercitation Through 2000
Howard White Barry Wellman, 2003 Does
Citation Reflect Social Structure
Strongest Globenet Co-Citation, Intercitation
Links Thru 2000
Duality of Persons Groups
  • People Link Groups
  • Groups Link People
  • An Interpersonal Net is an Interorganizational
  • Ronald Breiger 1973

The Dualities of Persons and Groups -- Graphs
Dualities of Persons and Groups -- Matrices
Dualities of Persons and Groups Event-Event
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
  • The disparity increases greatly as N increases
  • However, many of these subgroups are very similar

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
  • Block Modeling
  • Similar Role Relationships, Not Necessarily
  • Canada Mexico in Same Block US Dominated

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

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)

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
  • Easier to Decompose Whole Network
  • (Haythornthwaite Wellman)
  • Often Relies on Respondents Reports

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?

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

Multilevel AnalysisNew Approach to an Old
  • 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

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

Multilevel Analysis Network Effects
  • Network Size
  • Not Only More Support from Entire Network
  • More Probability of Support from Each Network
  • 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

Multilevel AnalysisCross-Level, Interaction
  • 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

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

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

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

Research Questions
  • Ties Does the Internet support all types of
  • Weak and Strong?
  • Instrumental and Socio-Emotional?
  • Online-Only or Using Internet Other Media (F2F,
  • Social Capital Has the Internet increased,
    decreased, or multiplied contact at work, in
  • 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?

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

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

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

Source Dan Heap Parliamentary Campaign 1992 (NDP)
Toronto in the Continental Division of Labor
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//
  • Barry Wellman, Physical Place and Cyber Place
    The Rise of Networked Individualism.
    International Journal of Urban and Regional
    Research 25 (2001) June.

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

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/
  • 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

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

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

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

The entrance to Netville
View of Netville
Wired and Non-Wired Neighboring in Netville
Neighboring Ties
  • Wired Residents
  • Recognize More
  • Talk with More
  • Invite More Into their Homes
  • And are Invited by Them
  • Neighbor in a Wider Area

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

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

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)
  • How the Internet Builds Local Community. City
    and Community, 2001

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

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

The Fishbowl Group Office
  • 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

  • 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
  • Social Control by Supervisor Group

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

  • 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

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

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
  • Does Email Move Spatial/Social Peripheries
    Socially Closer?
  • Does Email Foster Networked Organization?

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

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

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

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

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

  • 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

Indigo Work Interaction Time 1
Work Interaction (All Media) Prior to Telepresence
Indigo Work Interaction Time 3
Work Interaction (All Media) 14 months after
Telepresence Intro Greater Decentralization
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.

Netting Scholars Communities of Practice
  • 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,

Comparison of 2 Scholarly Networks
  • 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.

  • .
  • 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

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

  • 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

  • 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.

  • 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

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

Summary Ties
  • Internet Supports Strong Weak Ties
  • Evidence Netville, Netting Scholars, Cerise,
  • Internet Supports Instrumental Socioemotional
  • 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

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,
  • Demand for Local Information
  • Evidence Netville, Berkeley, Small City Study

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

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

SummaryComputer-Mediated Communication
  • Not only supports online virtual communities
  • Supports and maintains existing ties strong
  • 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

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

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
  • Shift from Spatial Propinquity to Shared
  • Shifting, Fluid Structures
  • Networked, Long-Distance Coordination Reports

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

ConclusionsRole-to-Role Relationships
  • Partial Communities of Shared, Specialized
  • Importance of Informal Network Capital
  • Production
  • Reproduction
  • Externalities
  • Bridging and Bonding Ties

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.

Conclusions Shift to New Kinds Of Community
  • 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

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

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

Design Considerations for a Networked Society
  • 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

Three Modes of Interaction Social Structure
Boundaries (continued)
Interpersonal Interactions
Social Networks
Norms and Perceptions
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

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

Edited Books
  • The Internet in Everyday Life
  • Caroline Haythornthwaite, co-editor
  • Oxford Blackwell Publishers 2002
  • Preliminary American Behavioral Scientist, Nov
  • 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

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
  • Research Supported By
  • Institute of Knowledge Management,
  • CITO, Mitel, National Science Foundation (US),
  • Social Science Humanities Research Council of

Thank You -- Barry Wellman
Networks For Ex-Newbies
  • Director, NetLabCentre for Urban
    Community StudiesUniversity of TorontoToronto,
    Canada M5S 1A1wellman_at_chass.utoronto.cawww.chass
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