Posts Tagged 'infection model'

Radicalisation as infection

I’ve argued in previous posts that the process of radicalisation is one that depends largely on properties of the individual, rather than on grand social or moral drivers — personality rather than society — and that it depends on the presence of an actual person (already radicalised) who makes the potential ideas real.

There is an alternative. Woo, Son, and Chen (J. Woo, J. Son, and H. Chen. An SIR model for violent topic diffusion in social media. In Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011, July 2011) show that radicalisation behaves a little bit like an infection (at least in the domain of ideas which they measure from forum postings). They show that the SIR (Susceptible-Infected-Recovered) model of disease transmission fits the data fairly well. In this model, members of a population begin in the susceptible state; they become infected with some probability A, and then recover with some probability B. After they’ve recovered they are no longer susceptible.

For the data they looked at, A was of the magnitude of 10^-4, so about 1 in 10,000 becomes infected. Once infected, B varied depending on the intensity of the topic from around 0.65 to 0.96. In other words, the probability of a ‘cure’ is well above a half, sometimes virtually certain.

This model suggests some interesting probabilities. First, it suggest that radicalisation is a state that can cure itself; in other words, we shouldn’t necessarily assume that once radicalised means always radicalised. Second, there may be a greater pool of people who pass through the stage of being radicalised but do not get it together to actually act on it before the fever breaks — perhaps because they don’t get the right training or the right opportunity at the time when they would exploit it if they could.

The numbers work out about right. There are around a million Muslims in the U.S. but the number who have (attempted to) carry out attacks is in the small number of dozens.