Familiar Strangers – Patterns in Our Daily Commute


Wherever you are in the world, if you’re a commuter on the subway whether on London Underground, the New York City Subway, taking the SkyTrain in Vancouver or on Paris’ Metro , some things are always the same.   Just as we have our morning set routines so does the person sitting opposite you.  Like you they most likely get the same train  or bus, like to sit in the same seat and spend their journey sleeping, listening to their iPod, reading a book or reading the same daily newspaper.

In many ways these people around you seem so familiar, and yet you know so little about them.   Now a new study in Singapore has tried to map and understand these daily interactions.

Using travel smart card anonymised data supplied by Singapore’s Land Transport Authority, the researchers from the Future Cities Laboratory, Singapore-ETH Centre for Global Environmental Sustainability looked at the bus journeys of almost 2.9 million individuals over a week; some 20 million bus trips – capturing almost 55% of the population of Singapore.

The researchers looked at the movements on all these individuals, and looked to see how these “familiar strangers” come across each other – so called “joint encounter patterns.”  And compared with other relationships that we have, for instance with friends which are driven by agreeing to meet at certain times and places, the meetings of “familiar strangers” is driven entirely by our own individual regularity.   The study reinforces earlier findings, taken from mobile phone records and travel diaries that as individuals our patterns of movement are remarkably regular and predictable.  We are to all intents and purposes creatures of habit.

So how likely is it that we’ll encounter the “familiar stranger”?

The study looked at the pattern of repeated joint encounters – when two individuals were on the same bus – and worked out an encounter networker, detailing how often two individuals were paired together and measured the time between two encounters of those people.

Perhaps not surprisingly, certain patterns began to emerge from the data. The times between joint encounters tended to be regular, and in around 85% of cases the encounter happened around the same time each day.  The study also showed that repeated encounters between two individuals tended to occur far more frequently in the morning than in the afternoon  – no doubt driven by our bosses demanding that we’re in work at the same time each morning, but our home time differing depending on whether we’re working late, meeting friends or have chores to run.


This study not only makes interesting reading in terms of gleaning an insight into our own social interaction and human behaviour, but it can help transit authorities understand better not only how we move as individuals but as a mass.  Planners can look at the ebbs and flows of human traffic – how we move around our transport networks, our supermarkets and shopping malls.

And with more and more devices being online, even underground as transport networks start installing wi-fi, companies like Google will be able to track devices in a similar fashion – using an ever richer set of data.  When two devices come together might we see how their users online habits are influenced by the world around them – as a bus passes a billboard for a new movie might Google track how many people respond by searching for it.  And might we see how ideas spread virally. How when a “familiar stranger” sees someone looking at a site on another user’s device then visits that themselves, and is then seen looking at that site themselves by another stranger who themselves goes on to visit it. And so on.

Although there’s clearly a need for data privacy the ability to track data in this way, and how we and our devices interact with others, could lead to a far better understanding of social science and collective human behaviour.

James Barnes,

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