The next step was to quantify how contagious the idea had been. Although the diagrams had originated in the US, they had spread quickly when they arrived in Japan. Things were more sluggish in the USSR, with a slower uptake than the other two countries. This was consistent with historical accounts. Japanese universities had expanded rapidly during the post-war period, with a strong particle physics community. In contrast, the emerging Cold War – combined with the scepticism of researchers like Landau – had stifled the diagrams in the USSR.
With the data they had available, Bettencourt and colleagues could also estimate the reproduction number, R, of a Feynman diagram: for each physicist who adopted the idea, how many others did they eventually pass it on to? Their results suggested a lot: as an idea, it was highly contagious. Initially R was around 15 in the USA and potentially as high as 75 in Japan. It was one of the first times that researchers had tried to measure the reproduction number of an idea, putting a number on what had previously been a vague notion of contagiousness.
This raised the question of why the idea had been so catchy. Perhaps it was because physicists were interacting with each other frequently during this period? Not necessarily: the high value of R instead seemed to be because people kept spreading the idea for a long time once they’d adopted it. ‘The spread of Feynman diagrams appears analogous to a very slowly spreading disease,’ the researchers noted. Adoption was ‘due primarily to the very long lifetime of the idea, rather than to abnormally high contact rates’.
Tracing citation networks doesn’t just tell us how new ideas spread. We can also learn how they emerge. If high profile scientists dominate a field, it can hinder the growth of competing ideas. As a result, new theories may only gain traction once dominant scientists cede the limelight. As physicist Max Planck supposedly once said, ‘science advances one funeral at a time.’ Researchers at MIT have since tested this famous comment by analysing what happens after the premature deaths of elite scientists.[7] They found that competing groups would subsequently publish more papers – and pick up more citations – while collaborators of the ‘star’ researcher tended to fade in prominence.
Scientific papers aren’t only relevant to scientists. Ed Catmull, co-founder of Pixar, has argued that publications are a useful way of building links with specialists outside their company.[8] ‘Publishing may give away ideas, but it keeps us connected with the academic community,’ he once wrote. ‘This connection is worth far more than any ideas we may have revealed’. Pixar is known for encouraging ‘small-world’ encounters between different parts of a network. This has even influenced the design of their building, which has a large central atrium containing potential hubs for random interactions, like mailboxes and the cafeteria. ‘Most buildings are designed for some functional purpose, but ours is structured to maximize inadvertent encounters,’ as Catmull put it. The idea of social architecture has caught on elsewhere too. In 2016, the Francis Crick Institute opened in London. Europe’s largest biomedical lab, it would become home to over 1,200 scientists in a £650 million building. According to its director Paul Nurse, the layout was designed to get people interacting by creating ‘a bit of gentle anarchy’.[9]
Unexpected encounters can help spark innovation, but if companies remove too many office boundaries, it can have the opposite effect. When researchers at Harvard University used digital trackers to monitor employees at two major companies, they found that the introduction of open-plan offices reduced face-to-face interactions by around 70 per cent. People instead chose to communicate online, with e-mail use increasing by over 50 per cent. Increasing the openness of the offices had decreased the number of meaningful interactions, reducing overall productivity.[10]
For something to spread, susceptible and infectious people need to come into contact, either directly or indirectly. Whether we’re looking at innovations or infections, the number of opportunities for transmission will depend on how often contacts occur. If we want to understand contagion, we therefore need to work out how we interact with one another. However, it’s a task that turns out to be remarkably difficult.
‘Thatcher halts survey on sex,’ announced the headline in The Sunday Times. It was September 1989, and the government had just blocked a proposal to study sexual behaviour in the UK. Faced with a growing hiv epidemic, researchers had become increasingly aware of the importance of sexual encounters. The problem was that nobody really knew how common these encounters were. ’We had no idea of the parameter estimates that would drive an epidemic of hiv,’ Anne Johnson, one of the researchers who’d proposed the UK study, later said. ‘We didn’t know what proportion of the population had gay partners, we didn’t know the number of partners that people had.’[11]
In the mid-1980s, a group of health researchers had come up with the idea of measuring sexual behaviour on a national scale. They’d run a successful pilot study, but had struggled to get the main survey off the ground. There were reports that Margaret Thatcher had vetoed government funding, believing that the study would intrude into people’s private lives, leading to ‘unseemly speculation’. Fortunately, there was another option. Shortly after The Sunday Times article came out, the team secured independent support from the Wellcome Trust.
The National Survey of Sexual Attitudes and Lifestyles – or Natsal – would eventually run in 1990, then again in 2000 and 2010. According to Kaye Wellings, who helped develop the study, it was clear the data would have applications beyond STIs. ‘Even as we were writing the proposal, I
