The social networking game

Our lives are dominated by social interactions that seem to be getting ever thicker.  We make new friends in real world, follow people on Twitter, circle people on G+, and add “friends” to our Facebook pages, to name a few.  What governs how we behave in these and other social situations?  And why do we have so many “friends”?

Turns out, we’re nicer when we get to pick our friends.  As for why we’ve got so many, it’s probably because there’s relatively little risk to expanding our network online.  When the stakes are higher, people tend to limit their interactions to people who are nice to work with.

These findings come from social experiments using the classic strategy game, the Prisoner’s Dilemma.  The game is played over multiple rounds, and in each round players choose between cooperating and defecting.  There’s fallout from either decision, based on the player’s action and the actions of his associates.  The game can be mapped to social, business, political, evolutionary, and environmental situations.

In this particular version of the game, dubbed “The Social Networking Game” by the researchers, players accumulated points based on their network of associates.  Points were assigned as follows, tallied throughout the game and players paid out based on their score:

Cooperator-cooperator:  4 pts each

Cooperator-defector:  -1 point to the cooperator, 7 pts to the defector

Defector-defector:  1 pt each.

Defectors in a sea of collaborators stand to be victors, but if everyone behaves that way, no one gets rich.  Each game went on for 12 rounds.  Between rounds, people could forge new bonds or sever existing ones.  In general, people chose to expand their networks with other cooperators and tolerated the few defectors, but those few bad apples eventually spoiled the barrel.

So the researchers modified the reward system to really penalize the cooperators for keeping those defectors around:

Cooperator-cooperator:  4 pts each

Cooperator-defector:  -5 point to the cooperator, 7 pts to the defector

Defector-defector:  -1 pt each.

Now people formed tight cooperating networks for almost the entire game (when players know how many rounds are in the game, they switch to defecting at the end in a last-ditch points effort).  Furthermore, early defectors were swiftly booted from the circle and essentially ostracized.

So what does it all mean?

In casual social situations, when we get to choose our colleagues and prune our social networks, we tend to wind up in groups that are highly collaborative. Especially when there are serious consequences for acting selfishly.  Of course, we can’t always choose who we work with, and these findings apply to decision-making in a wide variety of interactions.  But in a day-to-day context, putting ourselves in situations that allow for updating our networks probably has some social benefit.  Online social networks are a paradigm of picking who your friends are and pruning your network.  It’s sort of this experiment on a grand scale.  Perhaps, then, part of social media’s attraction?

Image credit:

Reference:  Cooperation and assortivity with dynamic partner updating.  J Wang, S Suri, DJ Watts.  PNAS, epub Aug 17th, 2012- open access publication.

Let the musical (r)evolution begin

The noise was fit enough to reproduce, so its genes were passed on to its daughters.

Can we use the scientific method to understand how music evolves?  Evolution, with all the trappings of tenth grade biology: heritable traits, genetic recombination and mutation, and survival of the fittest?  To find out, scientists in London and Japan wrote DarwinTunes, a computer program that applied the tenets of evolution to 8-second loops of computer-generated noise.  Then they watched as popular choice turned noise into music.

The noises were assigned a “genetic code” that could be shuffled around and mutated, much like our DNA.  Thousands of people voted on how much they liked (or hated) the noises.  The best loops were allowed to “reproduce,” or pass on their traits to the next generation.  Then people voted again.  This cycle went on for more than 2500 generations.  Through this process of (quasi-)natural selection, the researchers found that music quickly came from noise, complete with western rhythm and chordality.   You can listen to the evolution for yourself, here.

But then it stopped evolving.

Computer simulations aren’t the only place that musical change has plateaued.  It’s happening in real life, too. Scientists in Spain analyzed almost half a million popular songs recorded from 1955-2010, looking for changes in pitch (harmony, chords, melody), timbre (instruments used), and loudness (not how loud you blast it in your headphones, rather intrinsic loudness).  They analyzed these three traits within songs and across time.

The results are in.  If you grumble every time you turn on the radio, prepare your soapbox.  Newer songs basically sound the same, with simpler chord progressions and less instrumental variety.  Not only is this uninspiring to listeners, it could prove problematic for song recognition programs.  As for what has changed:  everything keeps getting louder.

Maybe social media will save us.  Yes, popular songs have the same ring.  But we have an Internet full of digital music.  As people explore and share songs that fall outside of this homogenous norm, we will probably see musical evolution pick up again.  Which gets back to the role of the audience in shaping new music.  As the creators of DarwinTunes point out, the line between audience and artist is easily blurred in our digital day and age.  Digital music allows people to tweak and re-share the original piece.  Audience-induced mutations could introduce a selective advantage that evolution just might favor.  Or, put more simply, seek out music that’s different, and mix up the stuff that’s not.


Photo credit:  Mark Runyon/

Original Papers:

Evolution of Music by Public Choice.  MacCallum et al.  PNAS July 24, 2012 vol. 109 no. 30 12081-12086

Measuring the Evolution of Contemporary Popular Western Music.  Serra et al.  Scientific Reports 2, Article #521.  July 26, 2012.  DOI:10.1038/srep00521