Essay by Manuel Cebrian, Iyad Rahwan, Victoriano Izquierdo, Alex Rutherford, Esteban Moro and Alex (Sandy) Pentland: “Our ability to search social networks for people and information is fundamental to our success. We use our personal connections to look for new job opportunities, to seek advice about what products to buy, to match with romantic partners, to find a good physician, to identify business partners, and so on.
Despite living in a world populated by seven billion people, we are able to navigate our contacts efficiently, only needing a handful of personal introductions before finding the answer to our question, or the person we are seeking. How does this come to be? In folk culture, the answer to this question is that we live in a “small world.” The catch-phrase was coined in 1929 by the visionary author Frigyes Karinthy in his Chain-Links essay, where these ideas are put forward for the first time.
Let me put it this way: Planet Earth has never been as tiny as it is now. It shrunk — relatively speaking of course — due to the quickening pulse of both physical and verbal communication. We never talked about the fact that anyone on Earth, at my or anyone’s will, can now learn in just a few minutes what I think or do, and what I want or what I would like to do. Now we live in fairyland. The only slightly disappointing thing about this land is that it is smaller than the real world has ever been. — Frigyes Karinthy, Chain-Links, 1929
Then, it was just a dystopian idea reflecting the anxiety of living in an increasingly more connected world. But there was no empirical evidence that this was actually the case, and it took almost 30 years to find any.
In 1967, legendary psychologist Stanley Milgram conducted a ground-breaking experiment to test this “small world” hypothesis. He started with random individuals in the U.S. midwest, and asked them to send packages to people in Boston, Massachusetts, whose address was not given. They must contribute to this “search” only by sending the package to individuals known on a first-name basis. Milgram expected that successful searches (if any!) would require hundreds of individuals along the chain from the initial sender to the final recipient.
Surprisingly, however, Milgram found that the average path length was somewhere between five point five and six individuals, which made social search look astonishingly efficient. Although the experiment raised some methodological criticisms, its findings were profound. However, what it did not answer is why social networks have such short paths in the first place. The answer was not obvious. In fact, there were reasons to suspect that short paths were just a myth: social networks are very cliquish. Your friends’ friends are likely to also be your friends, and thus most social paths are short and circular. This “cliquishness” suggests that our search through the social network can easily get “trapped” within our close social community, making social search highly inefficient.
Again, it took a long time — more than 40 years — before this riddle was solved. In a 1998 seminal paper in Nature, Duncan Watts & Steven Strogatzcame up with an elegant mathematical model to explain the existence of these short paths. They started from a social network that is very cliquish, i.e., most of your friends are also friends of one another. In this model, the world is “large” since the social distance among individuals is very long. However, if we take only a tiny fraction of these connections (say one out of every hundred links), and rewire them to random individuals in the network, that same world suddenly becomes “small.” These random connections allow individuals to jump to faraway communities very quickly — using them as social network highways — thus reducing average path length in a dramatic fashion.
While this theoretical insight suggests that social networks are searchable due to the existence of short paths, it does not yet say much about the “procedure” that people use to find these paths. There is no reason, a priori, that we should know how to find these short chains, especially since there are many chains, and no individuals have knowledge of the network structure beyond their immediate communities. People do not know how the friends of their friends are connected among themselves, and therefore it is not obvious that they would have a good way of navigating their social network while searching.
Soon after Watts and Strogatz came up with this model at Cornell University, a computer scientist across campus, Jon Kleinberg, set out to investigate whether such “small world” networks are searchable. In a landmark Nature article, “Navigation in a Small World,” published in 200o, he showed that social search is easy without global knowledge of the network, but only for a very specific value of the probability of long-range connectivity (i.e., the probability that we know somebody far removed from us, socially, in the social network). With the advent of a publicly available social media dataset such as LiveJournal, David Liben-Nowell and colleagues showed that real-world social networks do indeed have these particular long-range ties. It appears the social architecture of the world we inhabit is remarkably fine-tuned for searchability….
Some recent efforts have been made to try and disincentivize sabotage. If verification is also rewarded along the recruitment tree, then the individuals who recruited the saboteurs would have a clear incentive to verify, halt, and punish the saboteurs. This theoretical solution is yet to be tested in practice, and it is conjectured that a coalition of saboteurs, where saboteurs recruit other saboteurs pretending to “vet” them, would make recursive verification futile.
If we are to believe in theory, theory does not shed a promising light on reducing sabotage in social search. We recently proposed the “Crowdsourcing Dilemma.” In it, we perform a game-theoretic analysis of the fundamental tradeoff between the potential for increased productivity of social search and the possibility of being set back by malicious behavior, including misinformation. Our results show that, in competitive scenarios, such as those with multiple social searches competing for the same information, malicious behavior is the norm, not an anomaly — a result contrary to conventional wisdom. Even worse: counterintuitively, making sabotage more costly does not deter saboteurs, but leads all the competing teams to a less desirable outcome, with more aggression, and less efficient collective search for talent.
These empirical and theoretical findings have cautionary implications for the future of social search, and crowdsourcing in general. Social search is surprisingly efficient, cheap, easy to implement, and functional across multiple applications. But there are also surprises in the amount of evildoing that the social searchers will stumble upon while recruiting. As we get deeper and deeper into the recruitment tree, we stumble upon that evil force lurking in the dark side of the network.
Evil mutates and regenerates in the crowd in new forms impossible to anticipate by the designers or participants themselves. Crowdsourcing and its enemies will always be engaged in an co-evolutionary arms race.
Talent is there to be searched and recruited. But so are evil and malice. Ultimately, crowdsourcing experts need to figure out how to recruit more of the former, while deterring more of the later. We might be living on a small world, but the cost and fragility of navigating it could harm any potential strategy to leverage the power of social networks….
Being searchable is a way of being closely connected to everyone else, which is conducive to contagion, group-think, and, most crucially, makes it hard for individuals to differentiate from each other. Evolutionarily, for better or worse, our brain makes us mimic others, and whether this copying of others ends up being part of the Wisdom of the Crowds, or the “stupidity of many,” it is highly sensitive to the scenario at hand.
Katabasis, or the myth of the hero that descends to the underworld and comes back stronger, is as old as time and pervasive across ancient cultures. Creative people seem to need to “get lost.” Grigori Perelman, Shinichi Mochizuki, and Bob Dylan all disappeared for a few years to reemerge later as more creative versions of themselves. Others like J. D. Salinger and Bobby Fisher also vanished, and never came back to the public sphere. If others cannot search and find us, we gain some slack, some room to escape from what we are known for by others. Searching for our true creative selves may rest on the difficulty of others finding us….(More)”
