Despite widespread MMR rumours in the UK during the early 2000s, media reports were very different on the other side of the channel. While MMR was getting bad press in the UK, the French media were speculating about an unproven link between the hepatitis B vaccine and multiple sclerosis. More recently, there has been negative coverage of the HPV vaccine in the Japanese media, while a twenty-year-old rumour about tetanus vaccines resurfaced in Kenya.[14]
Scepticism of medicine isn’t new. People have been questioning disease prevention methods for centuries. Before Edward Jenner identified a vaccine against smallpox in 1796, some would use a technique called ‘variolation’ to reduce their risk of disease. Developed in sixteenth-century China, variolation exposed healthy people to the dried scabs or pus of smallpox patients. The idea was to stimulate a mild form of infection, which would provide immunity to the virus. The procedure still carried a risk – around 2 per cent of variolations resulted in death – but it was much smaller than the 30 per cent chance of death that smallpox usually came with.[15]
Variolation became popular in eighteenth-century England, but was the risk worth it? French writer Voltaire observed that other Europeans thought that the English were fools and madmen to use the method. ‘Fools, because they give their children the smallpox to prevent their catching it; and madmen, because they wantonly communicate a certain and dreadful distemper to their children, merely to prevent an uncertain evil.’ He noted that the criticism went the other way too. ‘The English, on the other side, call the rest of the Europeans cowardly and unnatural. Cowardly, because they are afraid of putting their children to a little pain; unnatural, because they expose them to die one time or other of the small-pox.’[16] (Voltaire, himself a survivor of smallpox, supported the English approach.)
In 1759, mathematician Daniel Bernoulli decided to try and settle the debate. To work out whether the risk of smallpox infection outweighed the risk from variolation, he developed the first-ever outbreak model. Based on patterns of smallpox transmission, he estimated that variolation would increase life expectancy so long as the risk of death from the procedure was below 10 per cent, which it was.[17]
For modern vaccines, the balancing act is generally far clearer. On one side, we have overwhelmingly safe, effective vaccines like MMR; on the other, we have potentially deadly infections like measles. Widespread refusal of vaccination therefore tends to be a luxury, a side effect of living in places that – thanks to vaccination – have seen little of such infections in recent decades.[18] One 2019 survey found that European countries tended to have much lower levels of trust in vaccines compared to those in Africa and Asia.[19]
Although rumours about vaccines have traditionally been country-specific, our increasing digital connectedness is changing that. Information can now spread quickly online, with automated translations helping myths about vaccination cross language barriers.[20] The resulting decline in vaccine confidence could have dire consequences for children’s health. Because measles is so contagious, at least 95 per cent of a population needs to be vaccinated to have a hope of preventing outbreaks.[21] In places where anti-vaccination beliefs have spread successfully, disease outbreaks are now following. In recent years, dozens of people have died of measles in Europe, deaths that could easily have been prevented with better vaccination coverage.[22]
The emergence of such movements has drawn attention to the possibility of echo chambers online. But how much have social media algorithms actually changed our interaction with information? After all, we share beliefs with people we know in real life as well as online. Perhaps the spread of information online is just a reflection of an echo chamber that was already there?
On social media, three main factors influence what we read: whether one of our contacts shares an article; whether that content appears in our feed; and whether we click on it. According to data from Facebook, all three factors can affect our consumption of information. When the company’s data science team examined political opinions among US users during 2014–2015, they found that people tended to be exposed to views that were similar to theirs, much more so than they would have been if they had picked their friends at random. Of the content that these friends posted, the Facebook algorithm – which decides what appears on users’ News Feeds – filtered out another 5–8 per cent of opposing political views. And of the content people saw, they were less likely to click on articles that went against their political stance. Users were also far more likely to click on posts that appeared at the top of their feed, showing how intensely content has to compete for attention. This suggests that if echo chambers exist on Facebook, they start with our friendship choices but can then be exaggerated by the News Feed algorithm.[23]
What about the information we get from other sources? Is this similarly polarised? In 2016, researchers at Oxford University, Stanford University and Microsoft Research looked at the web browsing patterns of 50,000 Americans. They found that the articles people saw on social media and search engines were generally more polarised than the ones they came across on their favourite news websites.[24] However, social media and search engines also exposed people to a wider range of views. The stories might have had stronger ideological content, but people got to see more of the opposing side as well.
This might seem like a contradiction: if social media exposes us to a broader range of information than traditional news sources, why doesn’t it help dampen the echoes? Our reaction to online information might have something to do with it. When sociologists at Duke University got US volunteers to follow Twitter accounts with opposing views, they found that people tended to retreat further back into their own political territory afterwards.[25] On average, Republicans became more conservative and Democrats more liberal. This isn’t quite the same as the ‘backfire effect’ we
