Mechanistic model shows how much gossip is needed to foster social cooperation

Gossip often has a negative connotation, but imagine you are part of a group deciding on a job candidate to hire or a local political candidate to back. Candidates who get a good reputation by helping others may be more likely to receive help in the form of a job offer or endorsement, a feedback loop known as indirect reciprocity. Gossip can facilitate

Previous research has shown that people tend to cooperate more when they think their peers are gossiping about their behaviour, gossipallows people to avoid potential cheaters, and gossip can punish freeloaders. Yet little was understood about how much gossip is required to foster cooperation and how incorrect information impacts the effects of gossip.

Researchers in the Plotkin Research Group in Mathematical Biology in the School of Arts & Sciences studied this issue by creating a model that incorporates two sources of gossip: randomly selected people versus a single source. They show that there is a mathematical relationship between these forms of gossip—meaning that understanding gossip with a single source also allows them to understand gossip with peers—and developed an analytical expression for the amount of gossip required to reach sufficient consensus and sustain cooperation.

Their findings are published in Proceedings of the National Academy of Sciences.

“The study of the spread of social information and the study of the evolution of cooperative behaviour are very mature fields, but there hasn’t been as much work done to combine those,” says first author Mari Kawakatsu, a postdoctoral researcher in the lab of biology professor Joshua B. Plotkin, the paper’s senior author.

“By merging ideas from the two fields, we were able to develop a mechanistic model of how information spread can help cooperative behaviour.”

Co-author Taylor A. Kessinger, also a postdoctoral researcher with a background in physics, says this analysis bridges the critical gap in past work on no gossip, where everyone’s opinion is private and independent, and infinitely fast gossip with total agreement about reputations. Kessinger has also seen the central role that indirect reciprocity plays on X, formerly known as Twitter, and how disagreement about reputations and ingroup-outgroup dynamics can incentivize bad behaviour.

“Systems of morality and reputation help ensure that good actors get rewarded and bad actors get punished. That way, good behaviour spreads and bad behaviour doesn’t,” Kessinger says. “If you punish a bad actor, you need to be sure that other people agree they’re guilty of wrongdoing. Otherwise, they might see you as the bad actor. Gossip can be one way to accomplish this.”

Plotkin says while past work has taken the basic model of indirect reciprocity and added various complications, such as stereotyping, this paper goes back and fills a gap in the theory. The paper provides a quantitative model that explains how many rounds of gossip are sufficient for people to change their cooperative or noncooperative behaviours, he says.

The paper involves a game-theoretical model where an interaction takes the form of a donation game, with each “donor” choosing whether to cooperate with each “recipient” by paying a cost to provide a benefit. All individuals serve once each as donor and recipient. Each then privately assesses the reputation of every donor by assessing their action toward a randomly selected participant, and a period of gossip about reputations follows. Private assessments and gossip continue until reputations equilibrate.

The authors note that behavioural strategies vary. Some always cooperate, some always defect, and some discriminate, meaning they cooperate when the recipient has a good reputation and defect when the recipient has a bad one. The researchers found that both forms of gossip tend to increase agreement about reputations, which in turn improves the equilibrium reputations of discriminators.

So, if gossip runs long enough, discriminators can eventually outcompete cooperators and defectors, which is a good outcome because discriminators are highly cooperative with one another and stable against noncooperative behaviours.

The researchers further found that biased gossip, meaning the spread of false information, can either facilitate or hinder cooperation, depending on the magnitude of gossip and whether the bias is positive or negative. But as gossip becomes more prone to unbiased “noise,” the population must gossip for longer to stabilize the equilibrium.

Kawakatsu next wants to think about how information flow interacts with altruism. The paper also notes that future research could explore how the number of gossip sources impacts cooperation, the conditions that would cause a rift in how an individual is viewed, and how bias may be applied differently for in-group and out-group members.

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Credit of the article given to University of Pennsylvania

 


Statistically significant

When the statistician for UC Irvine’s innovative Down syndrome program retired last year, its researchers were left in a bind. The group is studying ways to prevent or delay the onset of Alzheimer’s-type dementia in people with Down syndrome, including examining possible links between seizures and cognitive decline.

“We were mid-study when we found ourselves with no statistician and little budget with which to pay one,” explains program manager Eric Doran.

Statistical analysis for the project was critical and especially difficult. Some of the subjects’ dementia had progressed to the point that they could no longer be tested on performance-based cognitive measures. They couldn’t respond to questions, making it hard for clinicians to evaluate them. But that resulted in missing data. How, then, could the team accurately quantify change over time and see whether seizures might play a role?

Enter Vinh Nguyen, then a doctoral student in statistics at the Donald Bren School of Information & Computer Sciences and now the new head of the UCI Center for Statistical Consulting, which aims to help researchers across campus and Orange County with such challenges. He proposed a model to gauge how quickly people were becoming untestable, instead of how fast they declined. Rather than including test scores – which would have been zero for those who couldn’t be quizzed – Nguyen designed a variable to show when they became unable to respond.

“My part of it was to help them find a way to look at patients with and without seizures, to see if those with seizures might have a shorter time before they became untestable,” he says. “That’s what we found.”Although the findings are preliminary, without his involvement they wouldn’t have been possible. The work resulted in a paper that has been accepted for publication in the Journal of Alzheimer’s Disease. Nguyen, as of October an assistant professor-in-residence of statistics, is a co-author.

“We’re very fortunate to have Vinh’s assistance,” Doran says. “Quite frankly, some of the statistical analysis he’s doing goes well beyond the skill level of even the most seasoned investigators. Vinh was able to pick up where our previous statistician left off, and he was pretty ingenious. His creative look at the data enabled us to complete our analysis.”

Nguyen was glad to help: “I’m excited to be involved in studies that not only advance science but also make a meaningful impact in people’s lives.”

He looks forward to doing more such work through the center, providing state-of-the-art statistical expertise in grant preparation, the design of studies and experiments, and data analysis. The center this spring will offer free statistical consulting for campus researchers via a course taught by Dr. Nguyen. Graduate students in the class will be assigned to projects based on their interests and skills.

“It’s a huge benefit to the university because it’s free, and it’s a huge benefit to the statistics graduate program because it gives our master’s and Ph.D. students a chance to exercise their knowledge and training in real-world applications,” Nguyen says. “Learning how to communicate, how to collaborate with folks outside your field – you can’t just lecture about that. It’s got to be a hands-on experience.”

Colleagues say Nguyen, 26 – whose research interests include survival analysis, robust statistical methods, sequential clinical trials and prediction – was the right choice to run the center.

“It’s a big set of responsibilities for someone so young, but he’s got the ability and maturity level to succeed,” says associate professor of statistics Dan Gillen, who directs statistics research at the Institute for Memory Impairments & Neurological Disorders. It was Gillen who introduced Nguyen, whom he was advising on his doctoral thesis, to the Down syndrome team. “Vinh understands the role of statistics across multiple branches of science, and he’s extremely good at translating a seemingly vague hypothesis into a precise statistical framework.”

A native of Vietnam, Nguyen immigrated to the United States at age 5 and grew up in Garden Grove. A true-blue Anteater, he earned all his degrees at UCI, graduating magna cum laude with a B.S. in mathematics and a B.A. in economics, then obtaining an M.S. and a Ph.D. in statistics. In 2010, he received an Achievement Rewards for College Scientists scholar award, which recognizes UCI’s academically superior doctoral students who exhibit outstanding promise as scientists, researchers and public leaders.

“I feel very fortunate to be here,” Nguyen says. “I’m honoured to be given this opportunity to lead the center and help it grow, and to work in a field and a setting that allow me to apply my knowledge.”

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Credit of the article given to Rizza Barnes, University of California, Irvine