There is a concept in ecology called ‘optimal foraging theory’, which predicts that animals will attempt to maximise the number of calories they can ingest in a given unit of time.
The theory helps to predict the hunting patterns of predators, for example. They will invest time and effort in hunting and eating prey with high caloric content, or they will eat low-calorie prey if it is easy to catch.
Back in the late 1990s, Peter Pirolli of the Palo Alto Research Centre (PARC) noticed that Internet users search for information in much the same way.
Pirolli found that mathematical models developed to predict the movements of birds foraging for seed could also be used predict the behaviour of an individual searching for information online, including the moment they would give up on one webpage and start looking the desire information elsewhere.
This insight was used to develop a computer model that could navigate websites in a similar fashion to human beings.
In a 2009 paper, Pirolli developed a theoretical model for applying information foraging theory to social networks. It was really an investigation of whether such a model was possible, but the paper nevertheless made some thought provoking predictions.
For example, if a group is working together to discover information, the model predicts, it will only get better as the group grows if the diversity of its members also continues to grow. Also, individuals who link together separate ‘patches’ of information, i.e. fields of specialisation, will gain high social capital.
There are some characteristics of social collaboration that cannot be modeled using ‘foraging theory’, however, such as the trustworthiness and status of individuals. “When you go into the social realm… it’s more important to worry about credibility,” Pirolli recently told Monitor, a publication of the American Psychology Association. “You have to be in a position to judge who [people] are, what are their biases, can I trust them?”