The way we move and mobile phone viruses

By João Medeiros

One of the highlights of the “Science Beyond Fiction” conference in Prague was Lazlo Barabasi’s talk – “From Human Travel Patterns to Mobile Viruses”

Barabasi, author of the excellent book “Linked” , is one of the world experts on the topic of social networks.

In his talk, Barabasi presented novel insights about the science of human mobility patterns. The applications of such a study are incredibly wide-ranging, from understanding of how ideas and diseases spread, to the planning of traffic and urban spaces.

As one might guess, there is a huge element of randomness in the way we move.
Einstein, of course, was the first to theorize about random walk theory in the context of Brownian motion – the drunkard sailor paradigm (which constituted the first evidence for atoms).

The paradigm for how people move was first established by a series of studies by G.M.Vishwanathan on the mobility patterns of tagged birds and monkeys. What Vishwanathan found out was that animals do not follow the drunkard sailor pattern (ie, a Gaussian pattern) but instead follow a pattern compounded of lots of small steps with some big jumps, the so called Levy flight pattern, which is described as a power law distribution.

The first challenge in studying human mobility is how to get the data. Equipping millions of people with GPS track systems is prohibitively expensive (and probably ethically wrong).

But mobility data can be extracted from a variety of datasets which indirectly inform us of how we move.

For humans, this was first studied by Brockmann, who studied the motion of dollar bills (an explanation of their method can be found in their website whereisgeorge.com). What Brockmann found was that humans also obey the Levy flight pattern.
Barabasi also studied the mobility problem, using a mobile phone database composed of 7 million users, tracked between 2004 and 2009. His findings support the dollar bill findings.

Barabasi and collaborators (among whom is Cesar Hidalgo, who wrote a feature for PW last December) further discovered that the shape of human trajectories can be grouped into distinct categories according to typical ranges of motion, say one group for people who tend to move within a radius of 3 km, other for people who have radius of motion in the order of 100 km, etc.

What he found, was that within each category, the scaled patterns of motion are indistinguishable. This property – universality – means that all categories of human travelers can be described by one unified model.

This is important to understand many phenomena that derive from human mobility patterns. One such application is the understanding of mobile phone viruses.
Paradoxically, the first insight into the study of mobile phone viruses is to understand why mobile phone viruses are really not that relevant at the moment.

Experts estimate that there are approximately 600 varieties of mobile phone viruses. However, they exist only in smartphones, which, at the moment only detain 5% of the mobile phone marketshare.

These viruses spread in two ways. One, via Bluetooth, spreads in a manner similar to influenza, ie, related to physical proximity. The second mode of transmission is via MMS. These viruses spread in a manner akin to computer viruses and therefore have a capacity to spread non-locally.

In other words, the spread of Bluetooth virus depends on human mobility patterns, whilst MMS viruses depend on individual social networks. Understanding their modes of propagation leads us to understand their patterns of spreading. Simulations show that Bluetooth viruses may take days to reach everyone within a given region. MMS viruses, on the other hand, take only a matter of hours before reaching a maximum level of contagion. This saturation point is highly dependent on the level of market share of the smartphones.

MMS viruses are not dangerous below the level of 10% marketshare. Above that, however, we get a phase transition point and the virus can spread quickly everywhere within a matter of hours.

At the moment we are under that threshold, but when we reach that critical point, mobile phone viruses will become a serious threat to communications, especially since standard counter measures, such as anti-virus, are very difficult to install in smartphones due to the inherent memory capacity limitations on those phones.

Beyond the specific topic of mobile phone viruses, the work of Barabasi shows how mobile phones are quickly becoming a social experiment on itself, a gold mine of data in the study of social networks and human mobility patterns.