As well as debating the ethics of the experiment, the wider research community also raised concerns about the extent of emotional contagion in the Facebook study. Not because it was big, but because it was so small. The experiment had shown that when a user saw fewer positive posts in their feed, the number of positive words in their status updates fell by an average of 0.1 per cent. Likewise, when there were fewer negative posts, negative words decreased by 0.07 per cent.
One of the quirks of huge studies is that they can flag up very small effects, which wouldn’t be detectable in smaller studies. Because the Facebook study involved so many users, it was possible to identify incredibly small changes in behaviour. The study team argued that such differences were still relevant, given the size of the social network: ‘In early 2013, this would have corresponded to hundreds of thousands of emotion expressions in status updates per day.’ But some people remained unconvinced. ‘Even if you were to accept this argument,’ Salganik wrote, ‘it is still not clear if an effect of this size is important regarding the more general scientific question about the spread of emotions.’
In studies of contagion, social media companies have a major advantage because they can monitor much more of the transmission process. In the Facebook emotion experiment, the researchers knew who had posted what, who had seen it, and what the effect was. External marketing companies don’t have this same level of access, so instead they have to rely on alternative measurements to estimate the popularity of an idea. For example, they might track how many people click on or share a post, or how many likes and comments it receives.
What sort of ideas become popular online? In 2011, University of Pennsylvania researchers Jonah Berger and Katherine Milkman looked at which New York Times stories people e-mailed to others. They gathered three months of data – almost 7,000 articles in total – and recorded the features of each story, as well as whether it made the ‘most e-mailed’ list.[35] It turned out that articles that triggered an intense emotional response were more likely to be shared. This was the case both for positive emotions, such as awe, and negative ones like anger. In contrast, articles that evoked so-called ‘deactivating’ emotions like sadness were shared less often. Other researchers have found a similar emotional effect; people are more willing to spread stories that evoke feelings of disgust, for example.[36]
Yet emotions aren’t the only reason we remember stories. By accounting for the emotional content of the New York Times articles, Berger and Milkman could explain about 7 per cent of the variation in how widely stories were shared. In other words, 93 per cent of the variation was down to something else. This is because popularity doesn’t depend only on emotional content. Berger and Milkman’s analysis found that having an element of surprise or practical value could also influence an article’s shareability. As could the appearance of the story: an article’s popularity depended on when it was posted, what section of the website it was on, and who the author was. When the pair accounted for these additional characteristics, they could explain much more of the variation in popularity.
It’s tempting to think we could – in theory, at least – sift through successful and unsuccessful content to identify what makes a highly contagious tweet or article. However, even if we manage to identify features that explain why some things are more popular, these conclusions may not hold for long. Technology researcher Zeynep Tufekci has pointed to the apparent shift in people’s interests as they use online platforms. On YouTube, for example, she suspected that the video recommendation algorithm might have been feeding unhealthy viewing appetites, pulling people further and further down the online rabbit hole. ‘Its algorithm seems to have concluded that people are drawn to content that is more extreme than what they started with – or to incendiary content in general,’ she wrote in 2018.[37] These shifting interests mean that unless new content evolves – becoming more dramatic, more evocative, more surprising – it will probably get less attention than its predecessors. Here, evolution isn’t about getting an advantage; it’s about survival.
The same situation arises in the biological world. Many species have to adapt simply to keep pace with their competitors. After humans came up with antibiotics to treat bacterial infections, some bacteria evolved to become resistant to common drugs. In response, we turned to even stronger antibiotics. This put pressure on bacteria to evolve further. Treatments gradually became more extreme, just to have the same impact as lesser drugs did decades earlier.[38] In biology, this arms race is known as the ‘Red Queen effect’, after the character in Lewis Carroll’s Through the Looking-Glass. When Alice complains that running in the looking-glass world doesn’t take her anywhere new, the Red Queen replies that, ‘here, you see, it takes all the running you can do, to keep in the same place.’
This evolutionary running is about change, but it’s also about transmission. Even if a new mutation crops up in bacteria, it won’t automatically spread through a human population. Likewise, if new content emerges online, it’s not a guarantee it will become popular. We
