Contagion
How do we go about constructing the pipe?
The objective is to connect like-minded individuals together and enable them to expand the reach of the network. In that sense, it is akin to how a virus works – infect a person, then spread to others through the proximity contacts of that person, and thus cause contagion. Adam Kucharski writes about ‘R’, the reproduction number, in his book, The Rules of Contagion: “R depends on four factors: the duration of time a person is infectious; the average number of opportunities they have to spread the infection each day they’re infectious; the probability an opportunity results in transmission; and the average susceptibility of the population. I like to call these the ‘DOTS’ for short. Joining them together gives us the value of the reproduction number: R = Duration × Opportunities × Transmission probability × Susceptibility.”
In the context of ideas, Kucharski writes:
If we want an idea to spread, we ideally need people to be both highly susceptible and highly influential. But Aral and Walker found that such people were very rare. ‘Highly influential individuals tend not to be susceptible, highly susceptible individuals tend not to be influential, and almost no one is both highly influential and highly susceptible to influence,’ they noted. So what effect could targeting influential people have? In a follow-up study, Aral’s team simulated what would happen if the best possible people were chosen to spark a social outbreak. Compared with choosing randomly, the pair found that picking targets effectively could potentially help things spread up to twice as far. It’s an improvement, but it’s a long way from having a few little-known influencers who can spark a huge outbreak all by themselves.
Why is it so hard to get ideas to spread from person to person? One reason is that issue of people rarely being both susceptible and influential. If someone spreads an idea to lots of susceptible people, these individuals won’t necessarily pass it on much further. Then there’s the structure of our interactions. Whereas financial networks are ‘disassortative’ – with big banks connected to lots of small ones – human social networks tend to be the opposite. From village communities to Facebook friendships, there’s evidence that popular people often form social groups with other popular people. It means that if we target a few popular individuals, we might get a word-of-mouth outbreak that spreads quickly, but it probably won’t reach much of the network. Sparking multiple outbreaks across a network may therefore be more effective than trying to identify high profile influencers within a community.
So, if we have to build the distribution pipes for ideas, we need to focus on the components of R: duration, opportunities, transmission probability, and susceptibility. And we need to think not just of high profile influencers in a single community, but also reach multiple influencers in different communities. Think of them as the superspreaders who help increase the R. Our challenge is that we need to create a repeatable process out of this – and thus create a pipe through which ideas can flow regularly.
