information foraging from a network perspective — what
happens when people are connected to one another either
through online networks or the real world,” Pirolli says.
What often happens is that people can produce, learn
and synthesize more useful knowledge in groups than any
one of them could alone — and that has an analogy in the
natural world. Birds, lions and other animals live and forage
in groups. They do so because the advantages of sharing
information about a patch of foraging land can sometimes
outweigh the disadvantages of having to share your food with
“Group foraging can have a variety of advantages, one of
which is that it can provide much more rapid development of
precise information about an environment,” says Marc Mangel,
PhD, a theoretical ecologist at the University of California–
Santa Cruz, who has spent two decades studying mathematical
models of wildlife populations.
But, Mangel notes, animals’ groups won’t grow without
limits because at a certain point the disadvantages of sharing
food will, to an individual member, outweigh the advantages
of sharing information. Instead groups will expand until they
reach an optimal size, and then level off.
Pirolli and Mangel, working with colleagues at PARC and
UC–Santa Cruz, have recently been exploring an analogue
of this behavior in the online user-generated encyclopedia
Wikipedia. Wikipedia began in 2001, and until about 2007 the
site grew exponentially, as measured by the number of people
who contributed to it by writing and editing entries, and by the
number of total edits per month. But around 2007, the growth
began to slow down and level off.
In not-yet-published work, Mangel is looking at a series of
population models that ecologists have developed to describe
how wildlife populations grow, fluctuate and stabilize over time.
He’s studying how well these models fit observed data about the
growth of Wikipedia.
“In some sense, the rate of growth of any social network is
a balance between new individuals coming in and individuals
leaving for all sorts of reasons,” Mangel says. “In biology, we’d
say the rate of growth of a population is the balance between
births and deaths. We don’t exactly have births and deaths here,
but we do have new editors who are attracted for some reason,
and then we have a variety of processes that could cause people
Figuring out which models apply, and which processes are
most important, could suggest new ways to get more people to
participate in the site, Mangel says.
As Pirolli has turned his attention to the social Web, his research
interests have also moved beyond purely ecological models of
human behavior to a more general interest in how information
travels through social networks.
“Like a lot of analogies, [foraging theory] gives you a lot of
initial insight … but at some point the domain itself starts to
shape your theorizing,” he says.
And the domain of the social Web introduces some
complications to theories of how people look for information
“When you go into the social realm, now you have a whole
set of other judgments you have to make,” Pirolli says. “It’s
more important to worry about credibility. There are multiple
people giving you information, and you have to be in a
position to judge … who they are, what are their biases, can I
In one study, published in the proceedings of the 2011 IEEE
International Conference on Social Computing, Pirolli and his
colleagues examined how Twitter users decide which sources
of information to trust. The researchers asked 98 participants
to follow tweets from 60 different Twitter accounts. Of the 60
accounts, 10 each demonstrated expertise in cars, investing,
wine, fantasy football or dating. The other 10 accounts weren’t
experts in any particular area. Also, half of the accounts were
“high-status” — they had at least 10,000 followers on Twitter
— while the other half were “low-status,” with fewer than 200
Next, the researchers gave the participants information
about a used car and asked them to judge its value. Then, they
told the participants that one of the Twitter users had appraised
it at a particular price. Finally, they asked the participants
to estimate the car’s value again. The difference between the
initial and final estimate could be used as a measure of the
participant’s confidence in the credibility of the Twitter account.
The researchers found that credibility ratings were
influenced by both the content of the users’ tweets and their
social status in the network.
Finally, Pirolli and his colleagues used their data to develop a
model that could automatically rank the credibility of a Twitter
user on a particular subject, using a combination of key words
in his or her tweets, the number of followers he or she had, and
whether those followers were also interested in the relevant
Such a model could be used to help people narrow down
their sources of information in a social network and find the
most useful ones, according to Pirolli.
“One of the objectives we assume people have is that they
want to get the best information possible in the shortest
amount of time,” he says.
Helping people do just that, Pirolli believes, is where
psychologists have more to contribute to the field of
information systems than many realize.
“More and more often, these technologies are being
appropriated for things like health-care systems and work
productivity systems. This is where I think psychologists need
to have more impact. Otherwise it’s going to be built only by
engineers. It’s the classic problem with software — people will
build it without regard to how people actually use it.” n