Commuters generate close-knit social network

Every commuter knows them: people who you might nod at every morning, but whose name you don’t know. For the first time, Swiss researchers have helped paint a comprehensive picture of this secret network of familiar strangers.

Every commuter knows them: people who you might nod at every morning, but whose name you don’t know. For the first time, Swiss researchers have helped paint a comprehensive picture of this secret network of familiar strangers.

«I found it astonishing how much the number of familiar strangers varies from one person to the next,» said Kay Axhausen, a professor at the Institute for Transport Planning and Systems at the Federal Institute of Technology in Zurich (ETHZ).
 
He added that it was impressive to see that these individual networks ultimately merge into a large network: via two or three familiar strangers, every bus-user is connected to everyone else.
 
«It takes on average about three people to get from one end of that social network graph to the other. That’s very fast,» Axhausen notes.

How was it done?

The number of commuters is constantly on the rise and cities are growing bigger and bigger. Although this mobility and the encounters along the way have been part and parcel of everyday life for quite some time, until now researchers have not really been able to gather any comprehensive information on these commuter encounters.
 
For the first time, researchers from ETHZ and the National University of Singapore have described the network of encounters on public transport in the Asian five-million city state.
 
They employed a week’s data to track how often and on which routes people used the buses in Singapore. This was made possible thanks to a smart-card system, where passengers touch the card onto an electronic reader while alighting and descending from the bus and the price of the journey is deducted from their credit.
 
This enabled the researchers to gather data on the bus journeys for around three million individuals and ascertain who was on the same bus with whom, how often and for how long.

«The usual frame of reference in transport planning research is an average day,» says Axhausen. «Looking at a number of days is the exception because of the sheer cost of obtaining the data. That’s why the data set we got access to was so fascinating.»

«Secret social network»

Previous studies on social networks focused on contacts where the individuals already knew each other to a certain extent.
 
The new study, however, unveils a network of people who are aware of the existence of other individuals, see them repeatedly but don’t actually know them. The more frequent these encounters, the greater the familiarity and the greater the potential for two such familiar strangers to actually make contact, the researchers assume.
 
The secret social network that the researchers describe in the latest issue of the journal PNAS reveals how quickly infections could reach over half the population of Singapore via this route.
 
A totally different and completely harmless form of virulence exists in fashion trends and behaviour patterns, which can also spread via the network of familiar strangers. Something new tends to be increasingly accepted the more often it is seen on others, Axhausen explained.

«It is appropriate to talk of a social network in this context because you are exposed to the presence of others,» he says. «In many ways you will become aware of them over hte weeks and months of your usage of that (commuter) line – familiarity after a while with a face, awareness of how they dress and how they behave.»
 
Last but not least, rumours and news can also spread via such networks in that you might overhear a telephone conversation on the bus or train, for instance.
 
As the next step, the researchers would like to test whether what they have observed in Singapore also holds true for other cities. «It would be exciting to see whether our observations conform to an urban standard or whether Singapore is an exception,» Axhausen said.

And, their findings could have implications for further public health research into how quickly diseases spread across a population. According to Axhauser, other work by the same research group has already compared Singapore and Switzerland in this context.

«We simulated the spread of an influenza epidemic across Switzerland,» he said. «There, it took quite a number of days for an epidemic starting in Geneva to reach the east of the country. On an island like Singapore, it would spread much quicker.»

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