Social networks and gossip Jeroen Bruggeman 1 Cooperation

Social networks and gossip Jeroen Bruggeman 1

Cooperation? 2

Cooperation • Reputation: infomation [knowledge] that one individual has about another • Reputation: through observation and for humans - with language - also through gossip • Gossip requires network • Reciprocity as special kind of reputation -based cooperation 3

Reputations • Different reputations for different kinds of actions and skills • Let’s distinguish reputations for cooperation - as in game theory - from prestige for remainder actions and skills (gossip for both) • Meta-reputations for contributing to transmission of reputations 4

Gossip in theory • Who are trustworthy candidates to cooperate with? Whom to avoid? • Gossip as (evaluative) statements about non-present persons • Gossip-based reputations can foster cooperation, even for public goods (Panchanathan & Boyd 2004) • Boundary condition: actions observable 5

Gossip in actuality • Emotional aspects: irresistable to hear, gratifying to do • (Tacit) references to norms • Context dependent who can say what about whom • Diffusion in network, but locally sticky around gossipee • Conformist bias: (nearly) consensus within groups; not necessarily across 6

Gossip in actuality • Negative gossip does not necessarily create trust, but requires it: risk of retaliation when gossiper is exposed • Signaling group loyalty is self-serving without risk of sanctions: speak positively about group members who live up to group norms and negatively about norm violators 7

Gossip in actuality • Combined with self-presentation • Not always honest: strategic actions to make oneself look favorable compared with others (social comparison theory) • Meta-gossip about reliability and goals gossiper, e. g. excessive or unreliable gossip mongers are less trusted • Tactics: “the art of gossiping while not appearing to” N. Besnier 8

Can network topology reduce noise (error & manipulation) and increase trust? Appropriate definition of social cohesion to distinguish ‘better’ parts from ‘worse’ parts 9

Social cohesion as k-connectivity (Douglas White, Frank Harary 2001) • (sub)group bonding as strong as minimal number of (sub)group members, k, who hold group together • redundancy of information channels helps to reduce noise: minimal number of independent paths, m, that connect any pair of members • Theorem (Menger 1927): m = k 10

To be done: public goods experiment with imputed noise 3 -connected Gossip tuples (X, Y, ) 1 -connected, with same size, density, degree distribution, degree centralization, path distance 11

Complications • Through meta-reputations, people will trust some info-sources more than others - no adoption of average gossip but weighted average • In large groups, k-connectivity expected to have non-monotonic effect on cooperation. • Acutal networks change, probably also with non-monotonic effect 12