The next step will be to move beyond simply saying that contagion exists. Showing that behaviour can catch on is equivalent to knowing that the reproduction number is above zero: on average, there will be some transmission, but we don’t know how much. Of course, this is still useful information, because it shows contagion is a factor we need to think about. It tells us the behaviour is capable of spreading, even if we can’t predict how big the outbreak might be. However, if governments and other organisations want to address health issues that are contagious, they’ll need to know more about the actual extent of social contagion, and what impact different policies might have. If one person in a friendship group becomes overweight, exactly how much influence will it have on others? If you become happier, how much will your community’s happiness increase? Christakis and Fowler have acknowledged that it’s tricky to estimate the precise extent of social contagion. What’s more, addressing such questions often means using imperfect data and methods. But as new datasets become available, they point out others will be able to build on their analysis, moving towards an accurate measurement of contagion.
By studying potentially contagious behaviour, researchers are also uncovering some crucial differences between biological and social outbreaks. In the 1970s, sociologist Mark Granovetter suggested that information could spread further through acquaintances than through close friends. This was because friends would often have multiple links in common, making most transmission redundant. ‘If one tells a rumor to all his close friends, and they do likewise, many will hear the rumor a second and third time, since those linked by strong ties tend to share friends.’ He referred to the importance of acquaintances as the ‘strength of weak ties’: if you want access to new information, you may be more likely to get it through a casual contact than a close friend.[46]
These long distance links have become a central part of network science. As we’ve seen, ‘small-world’ connections can help biological and financial contagion jump from one part of a network to another. In some cases, these links may also save lives. There is a long-standing paradox in medicine: people who have a heart attack or stroke while surrounded by relatives take longer to get medical care. This may well be down to the structure of social networks. There’s evidence that close-knit groups of relatives tend to prefer a wait-and-see approach after witnessing a mild stroke, with nobody willing to contradict the dominant view. In contrast, ‘weak ties’ – like co-workers or non-relatives – can bring a more diverse set of perspectives, so flag up symptoms faster and call for help sooner.[47]
Even so, the sort of network structure that amplifies disease transmission won’t always have the same effect on social contagion. Sociologist Damon Centola points to the example of hiv, which has spread widely through networks of sexual partners. If biological and social contagion work in the same way, ideas about preventing the disease should also have spread widely via these networks. And yet they have not. Something must be slowing the information down.
During an infectious disease outbreak, infection typically spreads through a series of single encounters. If you get the infection, it will usually have come from a specific person.[48] Things aren’t always so simple for social behaviour. We might only start doing something after we’ve seen multiple other people doing it, in which case there is no single clear route of transmission. These behaviours are known as ‘complex contagions’, because transmission requires multiple exposures. For example, in Christakis and Fowler’s analysis of smoking, they noted that people were more likely to quit if lots of their contacts stopped as well. Researchers have also identified complex contagion in behaviours ranging from exercise and health habits to the uptake of innovations and political activism. Whereas a pathogen like hiv can spread through a single long-range contact, complex contagions need multiple people to transmit them, so can’t pass through single links. While small-world networks might help diseases spread, these same networks could limit the transmission of complex contagions.
Why do complex contagions occur? Damon Centola and his colleague Michael Macy have proposed four processes that might explain what’s happening. First, there can be benefits to joining something that has existing participants. From social networks to protests, new ideas are often more appealing if more people have already adopted them. Second, multiple exposures can generate credibility: people are more likely to believe in something if they get confirmation from several sources. Third, ideas can depend on social legitimacy: knowing about something isn’t the same as seeing others acting – or not acting – on it. Take fire alarms. As well as signaling there might be a fire, alarms make it acceptable for everyone to leave the building. One classic 1968 experiment had students sit working in a room as it slowly filled with fake smoke.[49] If they were alone, they would generally respond; if they were with a group of studious actors, they would continue to work, waiting for someone else to react. Finally, we have the process of emotional amplification. People may be more likely to adopt certain ideas or behaviours amid the intensity of a social gathering: just think about the collective emotion that comes with something like a wedding or a music concert.
The existence of complex contagions means we may need to re-evaluate what makes innovations spread. Centola has suggested that intuitive approaches for making things catch on may not work so well if people need multiple prompts to adopt an idea. To get innovation to spread in business, for example, it’s not enough to simply encourage more interactions within an organisation. For complex contagions to spread, interactions need to be clustered together in a way that allows social reinforcement of ideas; people may be more likely to adopt a new behaviour if they repeatedly see everyone in their team doing it. However, organisations can’t be too cliquey, otherwise new ideas
