The authors utilize cellphone data to measure the limit to which you can predict human movement.
They find that, despite the seemingly random movement of people across the world, people are extremely predictable and at any given time they typically will be in 1 or 2 locations (assumed to be home and work)
They also find that those who travel further distances on a regular basis are more predictable which they consider to be surprising.
Current models of human activity are fundamentally stochastic
Our goal here is to quantify the interplay between the regular and thus predictable and the random and thus unforeseeable, probing through human mobility the fundamental limits that characterize the predictability of human dynamics.
Mobile phone records collected by a phone company
3 months of data
50,000 cell phone users, selected from ~10 million users
Criteria for selection:
Visit more than two locations during the observed time period
Average call frequency is
Phone carriers record the location of the closest cell tower when he phone is utilized, from this they estimate a users geographical location
Fig 1 A, distinct travel maps of users travel to towers within an ~30-km range and another which travels to different towers in an ~90-km range
Fib 1B, the amount of time that a user spent in each region correlates with the size of the node in the network
Fig 1C, captures the temporal sequence of towers visited
Entropy is probably the most fundamental quantity of capturing the degree of predictability characterizing a time series.
They create three different measure of entropy, capturing three different aspects of the information that they've gathered from their data set
Random entropy —>
Temporal-uncorrelated entropy —>
Actual Entropy —>
Fig 1D, users tended to place most of their calls in short bursts, followed by long periods with no call activity — during which they have no information about the user's location — Fig 1C
Incompleteness of the data is represented by the variable (see Fig 1E)
Then they calculated all measures of entropy.
Find a stark difference between pure entropy and random entropy
Random entropy peaks at (bits of information)
Pure entropy peaks at which suggests that the real uncertainty in a typical user's whereabouts is not 64 but , i.e. fewer than two locations
The fundamental limit of each individual's predictability (how predictable they are)
Was found to narrowly peak at —> this means that we can predict with 93 % accuracy the future whereabouts of a user
This indicates that, despite the randomness of individual movement, we typically move in extremely predictable patterns
To nail down what was going on here, they broken the data down into hourly intervals and then identified the most visited location, within that hour
A users Regularity probability of finding the user in his/her most visited location during that hour
Fig 3A & B
across the entire dataset
This measure is time dependent, however...
We can see comparing A and B below, that ...
Fig 3C shows us that users with a larger travel radius actually have a higher level of relative predictability
In this paper the authors often seem surprised by the fact that an increased travel distance does not translate into a decreased predictability. However, to me this is exactly what I would expect.
People only travel large distances on a regular basis if they are doing so for their work. While some people certainly do travel long distances for other reasons, these typically would constitute traveling for holiday's and/or vacation, which would also be relatively predictable and, furthermore, relatively rare over a long enough temporal period.
Thus, if you accept this premise, their finding that those who travel further distances are more predictable makes perfect sense because, the unpredictability of an individuals movement seems to derive from when they are traveling for things other than work. If you are traveling two hours one way to work every day — you don't have the time, energy, or the desire to inject unpredictable movement into your everyday life.
People who do not travel far for work have more time to do spontaneous things and, thus, have more opportunity to increase the degree to which they can move randomly throughout the world.
Notes by Matthew R. DeVerna