A person reaches out to a stranger across town. That stranger will never return the favor: they'll never meet. So why help? Biologists call this indirect reciprocity: kindness comes back not from the person you helped, but from someone else, down the line.
In a new study, two variants of this idea were pitted against each other. The first is "upstream" help: I help because I was helped before. The second is "downstream" help: I help to build a good reputation. The authors built a computer model where agents live in a network, like people in a city, and can be selfish, experience-based helpers, or reputation-based helpers. At each step, someone changes their behavior based on their neighbors. And here's the twist: everything hinges on how information spreads. If news about actions travels instantly across the whole network, like gossip in a small village, reputation-based helpers win. But if everyone only knows their immediate circle, all three types coexist.
This is like adjusting volume: too quiet, you can't hear; too loud, it's noise. Same here: moderate connectivity creates islands of cooperation, protected from an invasion of selfishness but not completely isolated. The authors stress that although reputation sometimes suppresses personal experience, overall it still boosts mutual aid. You just need to set up the right channels for information about good deeds to flow through.
In real social networks, people typically have about five to six close contacts — almost like the "optimal six neighbors" from the model.