The Rules of Contagion

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