How teams benefit from communication policies: Information flow in human peer-to-peer networks

In an experiment involving teams of humans playing a cooperative game, We study the effect of local communication policies on the efficiency and the performance of teams and of individuals in different positions within a network. This design provides an experimental model of human communities, Where information may spread from peer to peer by word of mouth. With this model, We explain the realistic tradeoff between liberal information dumping and targeted information sharing by human peers. Human subjects exchanged natural-language messages with relevance to a task, Thereby sharing knowledge across a community. Communication took place along the edges of a small-world graph. Cooperation and individual efforts were incentivized. In one condition, Participants were asked to request specific information and only supply information that they knew was needed. In another condition, They were asked to supply and forward as much information as possible. We found that a targeted communication policy was successfully implemented by the participants, Increased task success, Shortened the time it took to get answers to questions, Increased efficiency (task success per communication bandwidth), And may have done so selectively for nodes with fewer connections.