COMMUNICATION in SMALL GROUPS
Instead of focusing on personal utility-maximization, small-group
communication experiments emphasize collective decisions / actions
This tradition seeks to explain small
group dynamics – both processes and
outcomes. For example, task-oriented
problem-solving; group morale; group
culture and collective identity; conflicts
and conflict resolution; co-evolution of
persons & groups in cooperative games.
Researchers also conduct field studies
of naturally forming groups and their
embeddedness within larger orgs
(e.g., workplace communication; shopfloor and executive-level teams) and
relations to the larger society (e.g.,
mass media and public opinion;
diffusion of innovations; theories of
public goods & free riding problems).
Small Group Lab
Studies of network effects on communication began at the MIT Small
Group Network Laboratory in 1940-50s with Alex Bavelas and Harold
Leavitt’s experiments on collective puzzle-solving tasks where five
subjects pass information via four cubicle-constrained configurations.
 At beginning, every subject possesses some unique info (5 of 6 symbols)
 Every S must discover which 5 symbols all the Ss have in common
 To solve, they pass written info through available slots in cubicle walls
 Experimenters measure whether the group solved the puzzle & how fast
Reinventing the Wheel
Both obvious & counter-intuitive findings emerged from experiments
Time: Wheel and Y were both much faster at
correctly solving puzzles than chain and circle
Messages: Wheel and Y passed fewest
messages; then chain; then circle
Leadership: Increasing belief that group had a
leader: circle, chain, Y, wheel (100%)
Satisfaction: Circle members enjoyed the task
most; followed by chain & Y; wheel least of all
Theoretically, a circle needs 4 transmissions to send one message to all, but
wheel needs at least 6. (Can you explain?) Why was wheel faster than circle?
Bavelas & Leavitt concluded that more centralized structures are more efficient.
Wheel and Y have an obvious leader, so no time is wasted in searching for a
strategy or vying for leadership. Everyone just funnels all info to the integrator.
But why are centralized group members less satisfied with their experience?
However, later experiments uncovered contingent relations:
(1) For simple tasks, wheel and Y have faster puzzle-solution times.
(2) For complex, ambiguous tasks, decentralized circle (also all-channel)
network structure is quicker at processing and integrating info.
Small Group Dynamics
After Kurt Lewin’s death, his MIT Center for Group Dynamics moved
in 1948 to University of Michigan’s Institute of Social Research.
Although a multidisciplinary unit, social psychologists dominated.
Several projects had a distinctly applied-research focus:

Acceptance of minority groups in the Dodge UAW union

Effects of discrimination on group morale & actions that
could overcome discrimination

Changes to improve worker morale, productivity, and job
satisfaction at the Michigan Bell Telephone Company
Outside academe, many “real-world”
training & consultancy orgs perpetuate
the tradition of applying small group
research findings to businesses, clubs,
government agencies, nongovernmental
organizations, even sports team & rock
bands. But the contributions of network
analysis to those efforts are unclear …
2-Step Flow of Communication
A bridge between micro- & macro-level communications began with
Paul Lazarsfeld’s studies of mass media influence on voting choices.
The People’s Choice (1944) found that opinion
leaders were important interpersonal mediators
of broadcast content. Lazarsfeld & Elihu Katz
(1955) formalized a model of the two-step flow
of communication: mass media messages are
filtered through & interpreted by more-exposed
central members of freely-forming local groups.
Finding Opinion Leaders
Opinion leaders occur in many domains, from politics to sports, culture
to fads-and-fashions. Marketers & advertisers frequently target them.
New Hampshire & Iowa lead
off presidential nomination
contests where “retail politics”
depends on small-group
influence, in contrast to later
primary contests where massmedia campaigns dominate.
Opinion leaders can be self-identified using network items in surveys:
1.
2.
3.
4.
5.
6.
During the past six months have you talked with anyone about the iPhone?
Compared with your circle of friends are you (a) more or (b) less likely to be asked for
advice about the iPhone?
Thinking back to your last discussion about iPhone, (a) were you asked for your
opinion of the iPhone or (b) did you ask someone else?
When you and your friends discuss new ideas about communication technology, what
part do you play? (a) Mainly listen or (b) try to convince them of your ideas.
Which of these happens more often? (a) You tell your friends and neighbors about
some new communication technology, or (b) they tell you about a new technology.
Do you have the feeling that you are generally regarded by your friend and neighbors
as a good source of advice about new communication technologies?
Kibitzing in a Kibbutz
Gabriel Weimann (1982, 1983) extended the two-step model, adding
network concepts to communication research in an Israeli kibbutz.
He examined the bridging function played by
marginally positioned people in mediating the
flow of information between groups. Results
supported balance theory and intransitivity
hypotheses about the structural advantages
of marginals in the communication flow.
He found that weak ties served as inter-group
bridges, confirming Granovetter’s “Strength of
Weak Ties” argument. Weak ties’ tendency
towards intransitivity & low multiplexity explain
those actors’ activation as intergroup bridges.
“The findings highlight the potential of social network analysis as a
bridge between micro-level interaction and macro-level patterns
including diffusion of innovation, formation of public opinion & social
solidarity. Weak ties serve as the crucial paths between groups, ... by
which individual behavior and ideas, originating in small face-to-face
groups, are routinized & agglomerated into large-scale patterns.”
Diffusion of Innovation among Physicians
Small networks are one mechanism through which information,
knowledge & innovations diffuse among members of communities
James S. Coleman, Elihu Katz, and Herbert Menzel (1957,
1966) studied the diffusion of tetracycline among 125
doctors in Decatur, IL. Altho Pfizer ran adverts in medical
journals, a network survey and pharmacy records revealed
adoption patterns depended more on social networks than
on mass communication. Physicians were asked to whom
they turned for advice & info? Discussed cases? Friends?
The more contacts, the more rapid the adoption of the new drug (next Figure).
“… networks of doctor-to-doctor contacts operated most powerfully in the first 5
months after the release of the new drug. … The discussion network and the
advisor network showed most pair-simultaneity at the very beginning and then
progressively declined. The friendship network … appears to reach maximum
effectiveness later.” No networks showed later-period effects beyond chance.
However, a reanalysis disputed this conclusion: after controlling for
Pfizer’s aggressive advertising of tetracycline, the alleged network
contagion effect vanished (van den Bulte & Lilien 2001)
Taking a Free Ride
Social trap occurs when individual choices that maximize utility
produce suboptimal collective outcome; e.g., tragedy of the commons
Mancur Olson’s (1965) Logic of Collective Action identified free rider constraint
on the creation of groups, resource contributions, & pursuit of collective goals.
Rational choice is to give only as much as one benefits
Temptation is to take a free ride on others’ efforts by
withholding contributions while someone else does
all the work (“Let George do it”)
But if all behave rationally, little or nothing gets done
Free riding is difficult to prevent in groups that seek
public goods – if the collective goal is achieved,
then no one can be excluded from its benefits
Does Neighborhood Crime Watch create security for all the residents?
When have you shirked participating, yet enjoyed fruits of others’ labor?
Hence, many groups must provide selective incentives – private goods
that members can obtain only when they join and participate in the org
Group Incentive Systems
Different types of organizations tailor particular combinations of
public goods and selective incentives that are consistent with
their members’ personal interests and group’s collective goals
Three basic types of incentives
 Utilitarian incentives: Private goods and direct services to
members that are consumed on an individual basis
 Social incentives: Jointly coordinated social & recreational
activities whose enjoyment is restricted to the membership
 Normative incentives: Primarily public goods requiring
collective efforts to influence governmental policy makers
What are some groups that you belong to? Which specific kinds of
benefits best induce potential members to join and contribute their
resources towards those groups’ public goods objectives?
How could network relations help to persuade people to change
their calculations about value of contributing time, money & effort?
Networks & Free Riding
An important Olson proposition is that free-riding will increase as
a group grows larger – shirking is less visible in a larger group.
But, social networks may overcome free
riding. Because an egocentric network is
smaller than a group’s size, if the number
of group members in ego’s network grows,
then ego is exposed to increasing social
incentives (“peer pressure”) to participate.
Social movements, cults, & voluntary associations often rely on
their members’ ego-nets to recruit new members. Solidarity with
one’s alters can be a potent social force to induce conformity.
Studying 569 members of a Swedish temperance movement org, 18961937, Sandell & Stern (1998) found that “additional members in the group
of relevant others increased a person’s propensity to join.” But, controlling
for ego-net composition, Olson’s free-rider hypothesis was also supported:
as the organization grew, the propensity to join the movement decreased.
An MTML Framework
Peter Monge & Noshir Contractor (2003) proposed an integrative
multitheoretical multilevel (MTML) framework of core mechanisms to
explain the evolution of complex adaptive communication networks.
They classified the core theories as
Self-Interest, Mutual Self-Interest and
Collective Action, Cognitive, Contagion,
Exchange & Dependency, Homophily
and Proximity, and Network Evolution.
MTML “seeks to examine the extent to which the structural tendencies
of organizational networks are influenced by multitheoretical
hypotheses operating at multiple levels of analysis.”
Exogenous
attributes of
actors
Exogenous
relations in
networks
Homophily implies preferred ties to
other actors sharing same attributes
Structure of
the focal
network
Endogenous mechanisms
H6: The network demonstrates a
structural tendency toward choice,
mutuality, transitivity, and … a
differential tendency toward choice of
other actors in the same block.
References
Coleman, James S., Elihu Katz, and Herbert Menzel. 1957. “The Diffusion of an Innovation among. Physicians.”
Sociometry 20: 253-270.
Coleman, James S., Elihu Katz, and Herbert Menzel. 1966. Medical Innovation: A Diffusion Study. Indianapolis:
Bobbs-Merrill.
Burt, Ronald S. 1987. “Social Contagion and Innovation: Cohesion Versus Structural Equivalence.” American Journal
of Sociology 92:1287-1335.
Burt, Ronald S. 1980. “Innovation as a Structural Interest: Rethinking the Impact of Network Position on Innovation
Adoption.” Social Networks 2:327-355.
Katz, Elihu, and Paul F. Lazarsfeld. 1955. Personal Influence: The Part Played by People in the Flow of Mass
Communication. Glencoe, IL: Free Press.
Lazarsfeld, Paul F., Bernard Berelson and Hazel Gaudet. 1944. The People’s Choice. NY: Columbia University Press.
Monge, Peter R. and Noshir S. Contractor. 2003. Theories of Communication Networks. NY: Oxford University Press.
Olson, Mancur. 1965. The Logic of Collective Action. Cambridge: Harvard University Press.
Sandell, Rickard and Charlotta Stern. 1998. “Group Size and the Logic of Collective Action: A Network Analysis of a
Swedish Temperance Movement 1896-1937.” Rationality and Society 10:327-345.
Van den Bulte, Christophe and Gary L. Lilien. 2001.“Medical Innovation Revisited: Social Contagion versus Marketing
Effort.” American Journal of Sociology 106:1409-1435.
Weimann, Gabriel. 1982. “On the Importance of Marginality: One More Step into the Two-Step Flow of
Communication.” American Sociological Review 47:764-773.
Weimann, Gabriel. 1983. “The Strength of Weak Conversational Ties in the Flow of Information and Influence.” Social
Networks 5:245-267.