Caro l ine Haythornthwai teL e v e r h u l m e T r u s t V i s i t i n g P r o f e s s o r ,

I n s t i t u t e o f E d u c a t i o n , U n i v e r s i t y o f L o n d o n

P r o f e s s o r , G r a d u a t e S c h o o l o f L i b r a r y a n d I n f o r m a t i o n S c i e n c e ,

U n i v e r s i t y o f I l l i n o i s

Social Networks and Learning4th Leverhulme Trust Public Lecture in a series on “Learning Networks”

My Background and Interests

How do people work, learn and socialize together at a distance and through computer media? Communication, Collaboration, Community

Studies : Online Learning Networks Social networks / virtual communities Distributed learners / e-learning Collaborative research teams / distributed knowledge Information sharing and learning / ubiquitous learning

Today: What kinds of interactions between people support learning and knowledge creation? Explore social network perspective and results of social

network studies of learners and collaborative research teams

Leverhulme Trust series on Learning Networks

Dec. 1, 2009 Learning in the age of Web 2.0

Feb. 4, 2010 Learning and scholarly communication in the age of the Internet

Feb. 23, 2010 New theories and perspectives on learning in the digital age

Mar. 11, 2010 Social networks and learning

Mar. 30, 2010 Social informatics: E-learning as a socio-technical intervention

May 10, 2010 Ubiquitous learning

For Slides, Texts, Reference

http://newdoctorates.blogspot.com/2009/10/leverhulme-trust-public-lectures.html

http://haythorn.wordpress.com/recent-activities/

SOCIAL NETWORKS

ONLINE NETWORKS

COMMUNICATION NETWORKS

SOCIAL NETWORKING

KNOWLEDGE NETWORKS

NETWORKED LEARNING

Networks

Networks are evident: In our buying habits

Touchgraphs using Amazon joint purchases re

‘social networks’

http://www.touchgraph.com/TGAmazonBrowser.html

In our organizing

Web links starting from Institute of Education, University of London

“Knowledge Map” based on probability of clicking between journals

In our reading

In our interactions

Connections among members of a science research team

Social Network Perspective

Not just social networking but a method for social analysis: social network analysis

A relational approach Emphasis on what people do together Who talks to whom about what?

Who gives, receives, shares what kinds of resources? A network approach

Attention to network structures and their outcomes How does the structure of a network affect resource

flow among group members? When do resources reach others? What resources can network members access?

Learning and Networks

Learning as a relation that connect people A student learns from a teacher Students learn together from a teacher Novices learn from each other

Learning as the outcome of relations A group acquires competence in technology use A community holds among its members a knowledge of

its history, and information resources for dealing with new situations

A society becomes proficient at supporting its citizens

Relational Approach to Learning

A relation is an interaction, transaction, communication, collaboration that ties two or more actors in a network Interactions between a teacher and students and

among students form the class social network Collaborating on projects forms stronger ties among

cliques within the class Learning from the same materials creates common

understanding and an indirect tie between learnersRelations are distinguised by content,

direction and strength

Actors in Networks

Individuals Adults, teens, children Employers, employees,

co-workersCollectives

Groups or Teams Organizations Communities

Other Governments Websites Documents

Actors in learning networks Teachers Students Administrators Schools, universities Co-workers Research teams Etc.

Relations: Content

Physical, emotional, or informational content that is transferred, exchanged, shared, or experienced

Communication Chatting, gossiping, giving information Instructions, commands, advice

Collaboration Working together, learning together

Social support Giving or receiving major or minor emotional support

Services Babysitting, lending small amounts of money, cleaning

up after disasters, helping neighbors

Relations: Direction and Strength

Direction of flow between actors Sent or received, given or received Information … from teachers, professionals to students,

novices Help with technology … from technological guru to co-

workers Social support … from parent to child, spouse to spouse Money … from parent to child

Strength of the relation How much, how often, and how important:

Intimacy, Frequency, Intensity, Quantity, Regularity, Longevity, Value

Defined both objectively and subjectively, e.g., minor versus major social support, monthly vs daily communication

Direct and Indirect Connection

Direct interaction A transfer of

information, goods, services between teacher and student supplier and customer employer and

employee A shared activity

colleagues working together

students learning from each other

Indirect interaction Attendance or

experience of a common event same lecture(s),

course, event Common knowledge

reading the same books, watching the same movies

Overlapping membership organizations and

institutions connected through common members of boards

Asking Network Questions

Asking People Who do you talk to … {about what}? Who did you hear about your job from? (Granovetter) Who do you discuss important matters with? (Burt)

U.S. general social survey question How often have you communicated with each

member of your work team in the last week?Interrogating Data

Who responds to whom in online conversations? What books are bought in common? (Amazon)

Learning Relations

Learning Know-what: facts from teachers, books, etc. Know-how: apprenticeships, informal learning Fiction: contagious diffusion of gossip and rumour Group: practices, who knows what (transactive memory), who knows

who knows what Education

Teaching, learning Evaluation: giving/handing in assignments, giving/ receiving grades Delivery of information: giving/attending lectures,assigning/reading

materials Community

Social support for learning, technology use Teaching by experts, learning by novices Learning community practices: culture, society, behavior, etc.

SN & Information

Transfers From one person to another, of factual information, social support,

skills, ideas, opinionsExchanges

Between two or more peopleCollaboration

Working or socializing together, co-construction of knowledgeCommon knowledge

Co-attendance at events, co-location in buildings Patterns of transfer, exchange, etc. reveal patterns showing

… Positions of actors in information space, and on information routes Roles of actors in creating, disseminating, receiving, holding, and

facilitating information flow or access to information Configurations of information flow

Relations define Ties

From Weak to Strong show increases in: Number and types of interaction Intimacy and reciprocity Attention and commitment to the relationship Frequency of interaction Number of means of communication used Motivation to share information and resources

Information sharing

Weak Ties . . . Acquaintances, friends of friends, casual contacts

Tend to be unlike each other Travel in different social circles

Information exchanges Infrequent, instrumental Few types of information or support Use of few media

. . . Strong TiesFriends, close friends, co-workers, team-mates

Tend to be like each other Travel in the same social circles

Information exchanges Frequent, multiple types, both emotional and instrumental High level of intimacy, self-disclosure, reciprocity in

exchanges Use of multiple media

Information sharing

Strength of weak ties … Experience / information /attitudes comes

from a different social sphere (Granovetter)But, low motivation and no obligation to

shareBridging social capital (Putnam; Lin)

… Strength of strong tiesMotivated – obliged – to share what resources

they haveBut, access to same resourcesBonding social capitalMultiple media use means more timely

communication, more self-directed

Actors + Relations Networks

Graph theory: Nodes and Connectors

Actors = nodes Relations and Ties =

connectors Networks =

configurations of nodes and connections

Social Network Analysis: Exploring Structure

Examining structural effects rather than aggregate behaviors

Rather than average of individual behaviors On average, group members send 20 emails a day

An assessment of interactional behaviors People who work together exchange 15 emails a day,

friends 10 per day, family 2 per day, other contacts 3 per day

Local work communications are centralized around one specific manager

Two employees talk frequently with each other but rarely with others

Networks

Networks

Egocentric perspectives

Personal networksEgocentric analyses Ego to each of his/her Alters, and relations between

alters

Personal Network of a Typical Distance Learner

Student

3 Strong Tiesdaily communication

All relations, including weeklyEmotional Support;

Maintained via 2 to 4 media, withvery high frequency

communication via Email

3 Intermediate to Strong Tiescommunication 2-3 times a week

2-4 relations, including low frequencyEmotional Support;

Maintained via 2 media

4 Weak to Intermediate Tiesweekly communication

2-4 relations, CW or EI plus Socializing,with occasional Emotional Support;Maintained via fewer than 2 media

Weak Ties with the Remainder of the Classmonthly communication

1-2 relations, mainly Collaborating on Class Work orExchanging Information, plus Socializing;

Maintained via 1 mediumusually the class medium (Webboard or IRC)

Triadic perspectives

Triads Simmelian Ties Pairs contained in complete

three-person cliques Members share more similar views of group structure

“Our guess is that … cliques lead to stronger ties and stronger ties lead to cliques in a reciprocating process that reinforces the relationship between Simmelian ties and agreement.” (Krackhardt & Kilduff, 2002, p. 288)

Collaborating on class work (at least 2 x a week over the semester)

B2

D3

B4

¬ D5 ¬

C8

D9

¬ B10 ¬

D12

C13C15

A6

A7

A11

A14

¬ Network Star, & Broker

Whole Networks

Networks show: density cliques network stars network brokers isolates isolated cliques structural holes resource flow social structure

Actor Level Measures

Who has the most direct connections to others in the network Degree centrality, Network stars

Who has the most outbound connections Influence

Who has the most inbound connections Prominence, popularity

Who has the least or no connections to others Isolates

B2

D3

B4

¬ D5 ¬

C8

D9

¬ B10 ¬

D12

C13C15

A6

A7

A11

A14

¬ Network Star, & Broker

Network Level Measures

Density What proportion of possible ties are actually present,

how cohesive is the network Example: 14 actors, 22 connections, density=.24

Caveat: dense does not necessarily mean best structure

Network centralization To what extent is the network organized around a

central core:Reachability

Can every member of the network be reached by some path

Path length What is the average number of actors it takes to get

information around the network

B2

D3

B4

¬ D5 ¬

C8

D9

¬ B10 ¬

D12

C13C15

A6

A7

A11

A14

¬ Network Star, & Broker

Subgroup Structures

To what extent is the network divided into subsets of connected actors

Cliques, clusters, components, k-plexes

Who connects 2 or more otherwise unconnected parts of the network Brokers, cutpoints

Who sits on the path through which most information will pass Betweenness

B2

D3

B4

¬ D5 ¬

C8

D9

¬ B10 ¬

D12

C13C15

A6

A7

A11

A14

¬ Network Star, & Broker

Social network studies of Collaboration and Learning

Results from Research Studies

My Major Studies

Co-located academic researchers Social networks and media use in a computer science

departmentDistributed learners

Longitudinal study of in-class interaction patterns and media use

Longitudinal qualitative study of the experiences of distance learners

Automated analysis of online conversations (current)Interdisciplinary science, social science and

education research teams Qualitative and questionnaire studies of collaboration and

learningTeachers

Qualitative and questionnaire studies of entrepreneurial behavior and networks (current)

Cerise: Co-located, Academic Researchers

Questionnaire 25 respondents (of 35 member group) answered 24

questions about a variety of their work and social interactions with 10-20 others within the group

Asked about relations and type of work and friendship tie

Factor analysis revealed six dimensions of work and social interaction reflecting Work practices : Receiving work (engaged in by 57% of

pairs); Giving work (57%) Major work products : Collaborative Writing (32%);

Computer Programming (56%) Social support relations : Sociability (86%); Major

Emotional Support (7% of pairs)

Sample Questionnaire FormatWho talks to whom about what and via which media?

Note: 24 questions x 25 respondents x 20 others produces 12,000 data points

LEEP: Distributed, Online Learners

[1] In-Class Social Networks Four classes of 14-23 students, two classes studied over

time Four questions re Collaboration on Class Work, Exchanging

Information or Advice about Class Work, Socializing, Exchanging Emotional Support

Type of Tie: Close friendship, Friendship, Work-only, Just another member of class

[2] Longitudinal Social Support Study 17 students from across the program, interviewed four times

over 1 year Exploring characteristics of online community

Learning to be part of an online program and community Particular attention to social support networks: who helped

them manage being “in school” online

Discovering Media Use is Related to Ties

[1] In-Class Social NetworksStudy revealed the importance of the tie between pairs and

the overall structure of media support in group interactionMedia Use

The closer the tie, the more media used – media multiplexity Media use follows a unidimensional scale consistent within each

group Media use is not associated with the content of the message

Networks of Media Use Patterns of ties and media emerge that describe tiers of media use

supporting networks of weak and strong ties Media are added to a pair’s repertoire in a unidimensional manner A “base” medium is evident that is established by an outside authority,

and its establishment creates a latent tie network on which ties may grow

Class F97: Collaborative work via IRC and Email by TimeInternet Relay Chat

Email

Group projects; Webboard also used for discussion, connected all to all.

Time 1 Time 2 Time 3

Time 1 Time 2 Time 3

Network Evolution

Egocentric Perspectives on E-Learners Networks

Personal NetworksEgocentric Network

Personal Network of a Typical Distance Learner

Student

3 Strong Tiesdaily communication

All relations, including weeklyEmotional Support;

Maintained via 2 to 4 media, withvery high frequency

communication via Email

3 Intermediate to Strong Tiescommunication 2-3 times a week

2-4 relations, including low frequencyEmotional Support;

Maintained via 2 media

4 Weak to Intermediate Tiesweekly communication

2-4 relations, CW or EI plus Socializing,with occasional Emotional Support;Maintained via fewer than 2 media

Weak Ties with the Remainder of the Classmonthly communication

1-2 relations, mainly Collaborating on Class Work orExchanging Information, plus Socializing;

Maintained via 1 mediumusually the class medium (Webboard or IRC)

Learning and Knowledge Exchanges

Interdiscipinary Research Teams 3 teams, qualitative and semi-structured interviews,

centred on interaction and learning from the 5-8 others with whom they interacted most frequently

Coded across all transcripts for learning exchanges Who do you learn from or receive help in understanding

something from? What do you learn from them or what kind of help do you get from them? e.g., learning or help in understanding techniques,

programming, factual knowledge? Who learns from you or who do you give help in

understanding something to? What do you convey to them? i.e., who do you teach, instruct, explain things to, give help in

understanding, writing, programming, analysis?

Learning Relations and Connections

Nine categories of learning in the three groups of interdisciplinary research teams Major:

Factual (Field) knowledge Process (how to) knowledge Method Joint research

Minor: Technology knowledge Socialization Generation of new ideas Networking Administration [very minor]

Network connections showed who talked to whom about these relations More Fact among

principal investigators More Method between

method specialistsSuggests learning

between groups happens along common domains of interest

Distribution of Learning Relations

Science, social science, and education teams

Data = Number of pairs maintaining each type of relation

1

10

11

12

13

14

15

1617

18

19

2

20

21

22

23

24

25

26

27

28

29

3

30

31

32

33

34

35

3637

38

39

4

40

41

42

43

44

45

46

47

48

49

5

50

51

52

6

7

8

9

Education team network13 respondents,

network of 29 actors (more junior personnel)

Network Configurations

Science team network

12 respondents, network of 52 actors(more senior personnel)

Networks based on who names who when asked for the 5-8 names of people inside and outside the specific team with whom they interact most frequently.

1

10

11

12

13

14

15

1617

18

19

2

20

21

22

23

24

25

26

27

28

29

3

30

31

32

33

34

35

3637

38

39

4

40

41

42

43

44

45

46

47

48

49

5

50

51

52

6

7

8

9

1

10

11

12

13

14

2

3

38

4

47

5

6

7

8

9

A ‘found’ core defined empirically As those with whom at least two respondents report a tie

Discovering Networks

Science team

Full and Core Network

HYPOTHESES ABOUT ORGANIZING PRINCIPLES BASED ON SOCIAL NETWORK

APPROACHMedia Mul t ip lex i ty

Latent T iesCrowds and Communi t ies

Summing Up

Organizing Principles

Online ties are ‘real’ ties Exhibit same characteristics as offline ties, plus new

multiplexity pattern of media useMedia multiplexity

Strongly tied pairs use more media to communicate than weakly tied pairs and within groups, media are added to ties in a common pattern associated with tie strength

Latent ties Media established by authorities provide the ground on

which weak ties may grow Changes in these media will have a greater effect on

weakly tied than on strongly tied pairsCrowds and communities (Leverhulme lecture #2)

(Online) Social Networks and Learning

Range of exchanges Social connections among learners include a range of

instrumental, task, social and support relations that need to be supported in e-learning and other collaborative knowledge environments

Exchange points Interdisciplinary knowledge in collaborative teams appears to

occur across comparable levels of interest – fact to fact; method to method

Media choices Media set as the main means of communication, whether face-to-

face classes or online chat become the key means of interaction for weak ties, and thus the conduit for new information

Questions?

References to Studies

Work and Social Relations in ‘Cerise’ Haythornthwaite, C. & Wellman, B. (1998). Work, friendship and media use for

information exchange in a networked organization. Journal of the American Society for Information Science, 49(12), 1101-1114.

Studies of ‘LEEP’ Networks Haythornthwaite, C. (2000). Online personal networks: Size, composition and media

use among distance learners. New Media and Society, 2(2), 195-226. Haythornthwaite, C. (2001). Exploring multiplexity: Social network structures in a

computer-supported distance learning class. The Information Society, 17(3), 211-226. ‘LEEP’ Qualitatitve

Haythornthwaite, C., Kazmer, M.M., Robins, J. & Shoemaker, S. (2000). Community development among distance learners: Temporal and technological dimensions. Journal of Computer-Mediated Communication, 6(1). http://jcmc.indiana.edu/vol6/issue1/haythornthwaite.html

Interdisciplinary Teams Haythornthwaite, C. (2006). Learning and knowledge exchanges in interdisciplinary

teams. Journal of the American Society for Information Science and Technology, 57(8), 1079-1092.

Overview papers Haythornthwaite, C. (2002). Strong, weak and latent ties and the impact of new

media. The Information Society, 18(5), 385 – 401. Haythornthwaite, C. (2005). Social networks and Internet connectivity effects.

Information, Communication & Society, 8(2), 125-147. Haythornthwaite, C. (2008). Learning relations and networks in web-based

communities. International Journal of Web Based Communities, 4(2), 140-158.

Further Reading on Social Networks

Wasserman, S. & Faust, K. (1994). Social Network Analysis. Cambridge University Press.

Wellman, B. (1997). Structural analysis: From method and metaphor to theory and substance. In B. Wellman & S.D., Berkowitz (Eds.), Social Structures: A Network Approach (pp. 19-61). Greenwich, CT: JAI Press.

Degenne, A. & Forsé, M. (1999). Introducing Social Networks. London: Sage. Kilduff, M. & Tasi, W. (2003). Social Networks and Organizations. London:

Sage. Monge, P.R. & Contractor, N.S. (2003). Theories of Communication Networks.

Oxford U. Watts, D.J. (2004). The “new” science of network. Annual Review of

Sociology,30,243-270. Borgatti, S.T., Mehra, A., Brass, D. & Labianca, G. (2009). Network analysis in

the social sciences. Science, 323, 892-895. Marin, A. & Wellman, B. (in press, 2010). Social Network Analysis: An

Introduction. In J. Scott & P. Carrington (Eds.), Handbook of Social Network Analysis. London: Sage.

Haythornthwaite, C. (2007). Social networks and online community. In A. Joinson, K. McKenna, U. Reips & T. Postmes (Eds.), Oxford Handbook of Internet Psychology (pp. 121-136). Oxford, UK: Oxford University Press.

Gruzd, A. & Haythornthwaite, C. (in press, 2010). Networking online: Cybercommunities. In J. Scott & P. Carrington (Eds.), Handbook of Social Network Analysis. London: Sage.