Social web: The great tipping point test
Social textile fabric: The great tipping point test
26 July 2010 by Mark Buchanan
Magazine number 2770. Subscribe and save
Read full article
Continue reading page |1 |2 |3
Editorial: Don't anxiety the tweeter: your data trail is doing good
Your online traces are helping firing material a revolution in the understanding of human behaviour – one that's revealing the precise laws of our lives
EVERY move you make, every twitter feeding mechanism you update, somebody is watching you. You may not think two times about it, but if you use a social networking site, a cellphone or the internet regularly, you are leaving in the rear a clear digital trail that describes your behaviour, travel patterns, likes and dislikes, divulges who your friends are and reveals your vein and your opinions. In short, it tells the world an awful lot about you.
Now, as any researcher will tell you, expert data is gold dust. Its absence leaves theories in the kingdom of speculation, and worse, poor data can lead you down dim alleys. Physics was the first science to be transformed by exact information, first with telescopes that revealed the heavens and culminating in ponderous modern-day experiments like the Large Hadron Collider at CERN, accurate Geneva, Switzerland. Biology was next, with genome sequencing throwing up in like manner much of the stuff that genetics has turned partly into one information science.
Now the study of human behaviour is heading the like way. Social scientists have long had to rely on crude questionnaires or interviews to congregate data to test their theories; methods marred by reporting bias and trivial survey sizes. For decades, the field has been looked down with by some as a poor cousin to the hard sciences. The digital vale of years is changing all that - practically overnight, the study of human behaviour and friendly interactions has switched, from having virtually no hard data to drowning in the trash. As a result, an entirely different approach to social science has emerged, and studies based on it are appearing with increasing frequency. The impact has been unusual.
"The data revolution is here for social science," says Albert-Lszl Barabsi of Northeastern University in Boston. "For the earliest time, scientists have a chance to study what humans do in certain time and in an objective way. It's going to fundamentally modify all fields of science that deal with humans."
The data whirling is here for social science. For the first time we can study what humans do in real time
It is becoming practicable to tackle fundamental problems previous generations have thought largely untouchable. As with every other data-rich science, Barabsi and his ilk ultimately object of trust to discover mathematical laws that describe human behaviour, and which could have existence used to predict what people will do.
Sociologists have been hunting for such laws about human interactions and social networks for decades, says Duncan Watts of Yahoo Research in New York, "nevertheless the far-reaching implications of their theories have been effectively impracticable to test. The measurement technology simply didn't exist". That's changing.
Watts was amid the first to realise the potential of the digital trail we license behind. In 2006, with his colleague Matthew Salganik, now at Princeton University, he designed a film-based experiment to examine how much social influence determines the favor of music. When a new song goes straight to number 1, it's unkind to know if its success has come from the song's adhering appeal, or instead from the herd-like behaviour of many the masses buying songs they think are already popular. The music industry has had niggard success in predicting which songs will do well and which won't, suggesting that a lot might be down to chance.
To examine what made some songs besides successful than others, Watts and Salganik created a project called Music Lab. It featured a website at what place more than 14,000 people listened to any of 48 songs ~ means of relatively unknown bands, rated them, and downloaded them if they wanted. These options on these terms a measure of quality (the average rating given) and popularity (the tell or downloads). Crucially, the duo were also able to control whether listeners could take heed how many times other people had downloaded any particular song, or in place had to rely solely on their own judgement. In this tendency of action, they could effectively compare outcomes with the power of social influence turned on or off. They also grouped the socially influenced participants into eight unrestricted "worlds" so that they could explore how the outcomes - the popularity rankings of the various tunes, based on downloads - might change admitting that the tape of history could be rewound and run again.
The results eagerly support the idea that human influence has a huge effect in structure some songs more popular than others. This factor also makes it plenteous harder to predict what will happen, and which songs will work well. The worlds in which social influence was operating had abundant higher inequality - with popular songs going up and unpopular songs going into a denser consistence to an even greater extent than in the worlds lacking sociable influence. With social influence turned on, song popularities fluctuated wildly betwixt one world to the next. So, like it or not, it seems like multiplied of us follow the herd.
Read full article
Continue reading boy-servant |1 |2 |3
Like what you've lawful read?
Don't miss out on the latest content from New Scientist.
Get New Scientist magazine delivered to your means, plus unlimited access to the entire content of New Scientist online.
Subscribe at present and save