COMMUNICATION in SMALL GROUPS

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; shop-floor 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).

Instead of focusing on personal utility-maximization, small-group communication experiments emphasize collective decisions / actions

Small Group LabStudies 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

Time: Wheel and Y were both much faster at correctly solving puzzles than chain and circleMessages: Wheel and Y passed fewest messages; then chain; then circleLeadership: 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?

Both obvious & counter-intuitive findings emerged from experiments

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 DynamicsAfter 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.

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 …

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

2-Step Flow of CommunicationA 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

1. During the past six months have you talked with anyone about the iPhone? 2. Compared with your circle of friends are you (a) more or (b) less likely to be asked for

advice about the iPhone? 3. 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? 4. 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. 5. 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. 6. 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?

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 mass-media campaigns dominate.

Opinion leaders can be self-identified using network items in surveys:

Kibitzing in a 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.

Gabriel Weimann (1982, 1983) extended the two-step model, adding network concepts to communication research in an Israeli kibbutz.

“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.”

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.

Diffusion of Innovation among PhysiciansSmall 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 RideSocial 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 SystemsDifferent 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 RidingAn important Olson proposition is that free-riding will increase as a group grows larger – shirking is less visible in a larger group.

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, 1896-1937, 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.

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.

An MTML FrameworkPeter 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.

Exogenous attributes of actors

Exogenous relations in networks

Structure of the focal network

Endogenous mechanisms

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.”

Homophily implies preferred ties to other actors sharing same attributes

H6: The network demonstrates a structural tendency toward choice, mutuality, transitivity, and … a differential tendency toward choice of other actors in the same block.

ReferencesColeman, 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.