Transcript The Argument

Barry Wellman
www.chass.utoronto.ca/~wellman
Seeing Networks
Barry Wellman, NetLab
Department of Sociology
University of Toronto
[email protected]
www.chass.utoronto.ca/~wellman
The Turn to Networked Individualism
Functioning in Encompassing , Densely-Knit,
Bounded Groups 
 Fragmented, Sparsely-Knit , Permeable &
Specialized Networks
 MyFace (sic) is only the most media-hyped aspect
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www.chass.utoronto.ca/~wellman
The Triple Revolution
The Internet Revolution
 The Mobile (Connectivity) Revolution
 The (Social) Network Revolution
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www.chass.utoronto.ca/~wellman
The Internet Revolution
Builds on and Reinforces the Network Revolution
 Instant Access to Diverse, Copious Information
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If You Know Much to Look
Rapid, Low-Cost Communication
Distance, Time Much Less of a Constraint
 Email as Frequent with Ties 3K km & 3 km
 Yet most ties are local – people have bodies!
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Supports Larger Networks
 Increasing Volume and Velocity of Info & Comm
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www.chass.utoronto.ca/~wellman
Social Affordances of New Forms of
Computer-Mediated Connectivity
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Bandwidth
Ubiquity – Anywhere, Anytime
Convergence – Any Media Accesses All
Portability – Especially Wireless
Globalized Connectivity
Personalization
www.chass.utoronto.ca/~wellman
Mobile Revolution
The Newest
 Information & Communication Available
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Wherever You Are
 Wherever You Go
 Always On, Always Connected
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Multiple Venues of Connectivity –
Social Venues
 Physical Venues – home, work, Starbucks
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www.chass.utoronto.ca/~wellman
The Network Revolution
The Subject of Our Talk
 Actually Came First
 We Think of Groups; We Function in Networks
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No longer densely-knit
 Fragmented – people switch & maneuver among nets
 Specialized role relationships
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•Social capital from boutiques & not general stores
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Premium on individual agency, rather than letting
the group do it
Find your own information – no more 2-step flow
 Maneuver/manipulate thru your networks.
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Traditional Ways of
Looking at Social Interactions
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Individuals as Aggregates of Attributes
All Possess One or More Properties
as an Aggregate of Individuals
 Examples: Sex, Education, Bank, Rich Countries
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Groups
(Almost) All Densely-Knit Within Tight Boundary
 Thought of as a Solidary Unit (Really a Special
Network)
 Family, Workgroup, Community, Association, Soviet
Bloc
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The Network Approach
 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, InterOrganizational, World-System, Internet
Nodes, Relationships & Ties
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Nodes: A Unit That Possibly is Connected
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Individuals, Households, Workgroups,Organizations, States
Relationships (A Specific Type of Connection)
A “Role Relationship”
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Ties (One or More Relationships)
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Friendship (with possibly many relationships)
Affiliations (Person – Organization)
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Gives Emotional Support
Sends Money To
Attacks
Works for IBM; INSNA Member; Football Team
One-Mode, Two-Mode Networks
www.chass.utoronto.ca/~wellman
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
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www.chass.utoronto.ca/~wellman
The Social Network Perspective
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Relations, not attributes
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No independence!
Dyadic relations operate in the context of
broader social structures
www.chass.utoronto.ca/~wellman
Networks Before Network-ing
Original ideas in the early 1900s – Georg Simmel
 First research in the 1930s – J.L. Moreno
 Modern Era of theory/research – mid 1960s:
Harrison White, etc.
 International Network for Social Network Analysis
founded at U of Toronto, 1976
 Email in late 1980s
 Networking software (Facebook) in this decade

www.chass.utoronto.ca/~wellman
Networks, Not Groups
“Groups” are a short-hand for special kinds of
networks:
cohesive, densely-knit & tightly-bounded
 Group = binary membership status
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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
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A Network Consists of One or More Nodes
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Connected by One or More Ties
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Could be One or More Relationships
That Form Distinct, Analyzable Patterns
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Could be Persons, Organizations, Groups, Nations
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,
ethnicity)
Although attributes may be correlated with
positions:
for example, central high-status white men
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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
The Multiple Ways of Network Analysis
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Method – The Most Visible Manifestation
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Data Gathering
Theory – Pattern Matters
Substance
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Add a Few Network Measures to a Study
Integrated Approach
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Community, Organizational, Inter-Organizational, Terrorist,
World System, Web
As an Add-On:
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Misleading to Confuse Appearance with Reality
A Way of Looking at the World:
Theory, Data Collection, Data Analysis, Substantive Analysis
Links to Structural Analyses in Other Disciplines
The Social Network Approach
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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
www.chass.utoronto.ca/~wellman
How Do Network Analysts Explain Things?
Some don’t. Pure formalists discovering structure
 How structure affects outcomes:
 Sparsely knit networks
provide a greater variety of resources
 Structure as providing constraints and
opportunities – manuverability of multiple clusters
 Structure matters more than individual attributes
 Structure helps explain individual motivations

www.chass.utoronto.ca/~wellman
Explanation by Structure Alone
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Understanding of motivation not necessary to
explain outcomes
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Harrison White: chains of opportunity (vacancy chains)
•Jobs, homes
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Structure as Constraint & Opportunity
People pursue their goals within structure
 Structure provides opportunities
to pursue goals & constraints on action
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e.g., Ron Burt’s Structural Holes
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Structural vs Other Explanations
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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
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www.chass.utoronto.ca/~wellman
Structure as Source of Motivations
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People “catch” peferences, goals, motivations, etc
from their networks:
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Epidemiology – attitudes to birth control; AIDs
Two methods:
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Cohesion – from those to whey are connected
•E.g., Poison Pills and Golden Parachutes
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Equivalence – From those in similar network positions
•Citation studies – White, Wellman & Nazer; Matzat
Changing Connectivity:
Groups to Networks
Densely Knit > Sparsely-Knit
 Impermeable (Bounded) > Permeable
 Broadly-Based Solidarity >
Specialized Multiple Foci
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www.chass.utoronto.ca/~wellman
Characteristics of a Networked Society
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Multiplicity of specialized relations
Management by networks
 More alienation, more maneuverability
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Loosely-coupled organizations / societies
Less centralized
 The networked society
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www.chass.utoronto.ca/~wellman
Little Boxes: Door-to-Door
 Old Workgroups/ Communities Based on
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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
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Little Boxes
GloCalization
Networked Individualism
BW, “From Physical Place
to Cyber Place”, Intl J of
Urban & Regional
Research, 2001
www.chass.utoronto.ca/~wellman
Place To Place: GloCalization
(Phones, Networked PCs, Airplanes, Expressways, RR, Transit)
Home, Office Important Contexts,
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Ramified & Sparsely Knit: Not Local Solidarities
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Not Intervening Space
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
Person To Person:
Networked Individualism
(Cell Phones, Wireless Computing)
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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
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Role To Role
Tailored Communication Media
 Little Awareness of Whole Person
 Portfolios of Specialized Relationships
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Boutiques, not Variety Stores
Cycling among Specialized
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Communities / Work Groups
Role-Based Media Interactions
 Management by Network
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www.chass.utoronto.ca/~wellman
The “Fishbowl” Group Office:
(Little Boxes)
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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
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No Real Secrets
No Secret Meetings
Anyone can Observe Conversations & Decide to Join
Little Alert to Others Approaching
www.chass.utoronto.ca/~wellman
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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
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The “Switchboard” Network Office:
Networked Individualism
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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
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Average Person knows > 1,000
Strangers & Friends of Friends May also be Contacted
www.chass.utoronto.ca/~wellman
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Sparsely-Knit
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Loosely-Bounded
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Most Don’t Know Each Other
Or Not Aware of Mutual Contact
No Detailed Knowledge of Indirect Ties
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
Little Boxes
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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/Alliances
 Cold War Blocs
 Fluid, Transitory Alliances
Ways of Looking at Networks
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Whole Networks & Personal Networks
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Focus on the System or on the Set of Individuals
Graphs & Matrices
We dream in graphs
 We analyze in matrices
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Network Data
Observation
 Archival
 Name Generators/Interpreters
 Position Generators
 Resource Generators
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www.chass.utoronto.ca/~wellman
What Do Network Data Look Like?
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Most quantitative data = one row per unit, with
variables representing unit's attributes
Respondent Sex Age Yrs Ed
1
0 18
2
1 54
3
1 38
4
0 28
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12
16
14
12
Network data = data about relations between units
We dream in graphs; we analyze in matrices
Whole Social Networks
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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?
www.chass.utoronto.ca/~wellman
Whole Networks vs. Ego Networks
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Personal Networks = the network surrounding one
person (node)
Person tied with Alters
 Alters’ characteristics
 Connections between alters
 Normally collected for multiple Egos
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Whole Networks = Network of a particular setting
or population. Bird's eye view of network, not
focused on one person
www.chass.utoronto.ca/~wellman
Network Graphs
Whole
Person
Costs of Whole Network Analysis
Requires a Roster of Entire Population
 Requires (Imposition of) a Social Boundary
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This May Assume What You Want to Find
Hard to Handle Missing Data
 Needs Special Analytic Packages
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Becoming Easier to Use
Duality of Persons & Groups
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People Link Groups
Groups Link People
An Interpersonal Net is an
Interorganizational Net
Ronald Breiger 1973
The Dualities of Persons and Groups -- Graphs
Network Size Matters
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(Robert) Metcalfe’s Law – (Xerox PARC, 1973)
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(David) Reed’s Law (MIT emeritus, 1997)
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For every network member added
The number of possible ties grows by N2
10 people => 102 possible ties = 100
For every network member added
The number of possible (sub)groups grows by 2N
10 people => 210 possible groups = 1,024
Not only does Reed give a higher number than Metcalf
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The disparity increases greatly as N increases
However, many of these subgroups are very similar
Personal Social Networks
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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)
Percentage of valid cases
Network Size:
The Myopia of “Bowling Alone”
40
30
20
10
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
5
15
25
35
45
55
65
# of network members
0
Very
Somewhat
Mean
Std. Dev.
Median
Very
11.6
7.2
10.0
Somewhat
12.2
8.4
10.0
Total
23.8
14.3
20.5
Social Network Analysis: More Flavors
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Diffusion of Information (& Viruses)
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Organizational Analyses
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“Real” Organization”
Knowledge Acquisition & Management
Inter-Organizational Analysis
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Flows Through Systems
Is There a Ruling Elite
Strategies, Deals
Networking: How People Network
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As a Strategy
Unconscious Behavior
Are There Networking Personality Types?
Branching Out (II)
Social Movements
 World-Systems Analyses
 Cognitive Networks
 Citation Networks
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Co-Citation
 Inter-Citation
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Applied Networks
Terrorist Networks
 Corruption Networks
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Web Networks
Multilevel Analysis:
Studying Emergent Properties
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Switching and Combining Levels
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Consider Wider Range of Theories
Disentangles (& Avoids Nagging Confounding)
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Individual Agency, Dyadic Dancing,
Network Facilitation & Emergent Properties
Tie Effects
Network Effects
Contingent (Cross-Level) Effects
Interactions
Addresses Emergent Properties
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Fundamental Sociological Issue
Simmel vs. Homans
Multilevel Analysis – Tie Effects
Tie Strength: Stronger is More Supportive
 Workmates: Provide More Everyday Support
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•(Multilevel Discovered This)
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
Multilevel Analysis:
Cross-Level, Interaction Effects
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Kinship
No longer a solidary system
 Parent-(Adult) Child Interaction
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•More Support From Each When > 1 Parent-Child Tie
•Single P-C Tie: 34%
•2+ P-C Ties, Probability of Support from Each: 54%
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
Research Questions
Ties: Does the Internet support all types of ties?
1.
1.
2.
3.
Social Capital: Has the Internet increased, decreased,
or multiplied contact – at work, in society?
2.
1.
2.
3.
3.
Weak and Strong?
Instrumental and Socio-Emotional?
Online-Only or Using Internet & Other Media (F2F, Phone)?
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 (cont’d)
4.
5.
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
www.chass.utoronto.ca/~wellman
Research Questions – re Memes
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Do Memes Preferentially Spread Locally?
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i.e., Does Face-to-Face Communication still Pay-Off?
Do Fragmented Networks  Localized Memes?
 How Do Memes Facilitate Within-Net & Cross-Net
Connectivity?
 Has Trust Declined with Multiple Venues & Lower
Interpersonal Bandwidth
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Summary: Local Social Capital
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Multiplied Number & Range of Neighbors
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Increased Contact with Existing Neighbors –
Email Adds On to Same Levels of F2F, Phone
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Evidence: Netville
Evidence: National Geographic, Berkeley, Netville?
Demand for Local Information
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Evidence: Netville, Berkeley, Small City Study
Summary: Long Distance Ties
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Increased Contact with Long Distance Ties –
Email Adds On to Same Levels of F2F, Phone
1. Friends More than Kin
2. Long-Distance Ties More than Local
3. Post Used Only for Rituals (Birthdays, Christmas)
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Evidence: National Geographic, Netville
Summary: Long Distance Ties
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Increased Contact with Long Distance Ties –
Email Adds On to Same Levels of F2F, Phone
1. Friends More than Kin
2. Long-Distance Ties More than Local
3. Post Used Only for Rituals (Birthdays, Christmas)
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Evidence: National Geographic, Netville
Summary: The GloCalization Paradox
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Surf and Email Globally
Stay Wired at Office/Home to be Online
Desire for Local/Distant Services and Information
Internet Supplements/Augments F2F
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Doesn’t Replace It;
Rarely Used Exclusively
Media Choice? By Any Means Available
Many Emails are Local –
Within the Workgroup or Community
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Local Becomes Just Another Interest
Evidence: Netville, National Geographic, Small Cities,
Berkeley, Netting Scholars, Cerise, Indigo, Telework
Summary: Social Network Structure
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Internet Aids Both Direct & Indirect Connections
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Knowledge Acquisition & Management
• Accessing Friends of Friends
• Forwarding & Folding In: Making Indirect Ties Direct Ties
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Social and Spatial Peripheries Closer to the Center
Shift from Spatial Propinquity to Shared Interests
Shifting, Fluid Structures
Networked, Long-Distance Coordination & “Reports”
Conclusions: Changing Connectivity
 By Any Means Available
 Door-to-Door > Place-to-Place
> 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
Conclusions:
Role-to-Role Relationships
Partial Communities of:
Shared, Specialized Interest
 Importance of Informal Network Capital
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Production
 Reproduction
 Externalities
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Bridging and Bonding Ties
Conclusions:
How 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. 179205 in Culture of the Internet, edited by Sara Kiesler.
Mahwah, NJ: Lawrence Erlbaum, 1997.
Conclusions: Shift to New Kinds
Of Community & Workgroups
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Partial Membership in Multiple Networks
Multiple Reports
Long-Distance Relationships
Transitory Work Relationships
Each Person Operates Own Network
Online Interactions Linked with Offline
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Status, Power, Social Characteristics Important
Sparsely-Knit: Fewer Direct Connections Than Door-To-Door -Need for Institutional Memory & Knowledge Management
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IKNOW (Nosh Contractor) – Network Tracer
ContactMap (Bonnie Nardi & Steve Whittaker) – Network Accumulator
Conclusions:
The Rise of Networked Individualism
 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
Three Modes of Interaction
Social Structure
Phenomena
Little Boxes
Glocalization
Networked
Individualism
Metaphor
Fishbowl
CorePeriphery
Switchboard
Unit of
Analysis
Village, Band,
Shop, Office
Household,
Work, Unit,
Multiple
Networks
Networked
Individual
Social
Organization
Groups
Home Bases
Network of
Networks
Networked
Individualism
Era
Traditional
Contemporary
Emerging
Boundaries
Phenomena
Little Boxes
Glocalization
Net. Individualism
Physical Context
Dominance of immediate
context
Relevance of immediate
context
Ignorance of immediate context
Modality
Door-to-Door
Place-to-Place
Person-to-Person
Predominant Mode
of Communication
Face-to-Face
Wired phone
Internet
Mobile phone,
Wireless modem
Spatial Range
Local
GloCal = Local + Global
Global
Locale
All in common household
and work spaces
Common household and
work spaces for core +
external periphery
External
Awareness and
Availability
All visible and audible to all
High awareness of
availability
Core immediately visible,
audible;
Little awareness of others’
availability -- must be
contacted
Little awareness of availability
Must be contacted
Visibility and audibility must be
negotiated
Access Control
Doors wide open to in-group
members
Walled off from others
External gate guarded
Doors ajar within and
between networks
Look, knock and ask
Doors closed
Access to others by request
Knock and ask
Physical Access
All have immediate access to
all
Core have immediate access
Contacting others requires a
journey or
telecommunications
Contact requires a journey or
telecommunications
Permeability
Impermeable wall around
unit
Household and workgroup
have strong to weak outside
connections
Individual has strong to weak
connections
Boundaries (continued)
Phenomena
Little Boxes
Glocalization
Net. Individualism
Interruptibility
High: (Open Door)
Norm of Interruption
Mixed: Core interruptible
Others require deliberate
requests
Answering machine
Knocking on door that may
be ajar or closed
Norm of Interruption within
immediate network only
Low: Contact must be
requested
May be avoided or refused
Prioritizing voice mail
Internet filter
Knocking on door that may be
ajar or closed
Norm of interruption within
immediate network only
Observability
High: All can see when other
group members are
interacting
Mixed: Core can observe core
Periphery cannot observe
core or interactions with
other network members
Low: Interactions with other
network members rarely visible
Privacy
Low information control:
Few secrets
Status/Position becomes
important capital
Low information control:
Few secrets for core
Variable information control
for periphery
Material resources and
network connections become
important capital
High information control:
Many secrets
Information and ties become
important capital
Joining In
Anyone can observe
interactions
Anyone can join
Interactions outside the core
rarely observable
Difficult to join
Interactions rarely observable
Difficult to join
Alerts
Little awareness of others
approaching
Open, unlocked doors
High prior awareness of
periphery’s desire to interact
Telephone ring, doorbell
High prior awareness of others’
desire to interact
Formal requests
Interpersonal Interactions
Phenomena
Little Boxes
Glocalization
Net. Individualism
Predominant Basis of
Interaction
Ascription (What you are born into)
e.g., Gender, ethnicity
“Protect Your Base Before You Attack”
(attributed to Mao)
Free agent
Frequency of Contact
High within group
Moderate within core;
Low to moderate outside of core
Variable, low with most;
Moderate overall
Recurrency
Recurrent interactions within group
Recurrent interactions within core;
Intermittent with each network
member
Low with most others;
Moderate overall
Duration
Long duration ties:
cradle-to-grave; employed for life
Long duration for household core
(except for divorce);
Short duration otherwise
Short duration ties
Domesticity
Cradle-to-grave
Mom and Dad
Dick and Jane
Long-term partners
Serial monogamy
Dick lives with divorced parent
Changing partners; Living together; Singles;
Single parents;
Nanny cares for Jane
Scheduling
Drop-In anytime
Drop-in within household, work core;
Appointments otherwise
Scheduled appointments
Transaction Speed
Slow
Variable in core; Fast in periphery
Fast
Autonomy &
Proactivity
Low autonomy
High reactivity
Mixed: Autonomy within household &
work cores
High proactivity & autonomy with
others
High autonomy
High proactivity
Tie Maintenance
Group maintains ties
Core groups maintain internal ties;
Other ties must be actively maintained
Ties must be actively maintained, one-byone
Predictability
Predictability, certainty and security
within group interactions
Moderate predictability, certainty and
security within core;
Interactions with others less
predictable, certain and secure
Unpredictability, uncertainty, insecurity,
contingency, opportunity
Latency
Leaving is betrayal;
Re-Entry difficult
Ability to reestablish relationships
quickly with network members not
seen in years
Ability to reestablish relationships quickly
with network members not seen in years
Social Networks
Phenomena
Little Boxes
Glocalization
Net. Individualism
#of Social Circles
Few: Household, kin, work
Multiple: Core household, work unit;
Multiple sets of friends, kin, work
associates, neighbors
Multiple: Dyadic or network ties with
household, work unit, friends, kin, work
associates, neighbors
Maneuverability
Little choice of social circles
Choice of core and
other social circles
Choice of social circles
Trust Building
Enforced by group
Betrayal of one is betrayal of all
Core enforces trust
Networked members depend on
cumulative reciprocal exchanges and
ties with mutual others
Dependent on cumulative reciprocal
exchanges and ties with mutual others
Social Support
Broad (“multistranded”)
Broad household and work core;
Specialized kin, friends, other work
Specialized
Social
Integration
By groups only
Cross-cutting ties between networks
integrate society;
Core is the common hub
Cross-cutting ties between networks
integrate society
Cooperation
Group cooperation
Joint activity for clear, collective
purposes
Core cooperation;
Otherwise: short-term alliances,
tentatively reinforced by trust building
and ties with mutual others
Independent schedules
Transient alliances with shifting sets of
others
Knowledge
All aware of most information
Information open to all within unit
Secret to outsiders
Core Knows Most Things
Variable awareness of and access to
what periphery knows
Variable awareness of and access to what
periphery knows
Social Control
Superiors and group exercise
tight control
Moderate control by core household
and workgroup, with some spillover to
interactions with periphery
Fragmented control within specialized
networks
Adherence to norms must be
internalized by individuals
Subgroups, cleavages
Partial, fragmented control within
specialized networks
Adherence to norms must be internalized
by individuals
Resources
Conserves resources
Acquires resources for core units
Acquires resources for self
Basis of Success
Getting along
Position within group
Getting along
Position within core; Networking
Networking
Filling structural holes between networks
Norms and Perceptions
Phenomena
Little Boxes
Glocalization
Net. Individualism
Socialization
Obey group elders
Obey your parents;
cherish your spouse;
nurture your children;
Defer to your boss; work
and play well with
colleagues and friends
Develop strategies and
tactics
for self-advancement
Sense of
Solidarity
High group solidarity
Collective identity
Collective name
Moderate solidarity
within core household
and workgroup,
Vitiated by many ties to
multiple peripheries
Sense of being an
autonomous individual
Fuzzy identifiable networks
Loyalty
Particularistic:
High group loyalty
Public and private
spheres:
Moderate loyalty to home
base
takes precedence over
weak loyalty elsewhere
Self
Global weak and divided
loyalties
Conflict Handling
Revolt, coup
Irrevocable departure
Back-biting
Keeping distance
Avoidance
Exit
Commitment to
Net Members
High within groups
High within core;
Variable elsewhere
Variable
Zeitgeist
Communitarian
Conflicted
Existential
www.chass.utoronto.ca/~wellman
Thanks for the Meme-ories
Barry Wellman