The Wellcome Trust has recently (yesterday) released the 2018 Global Monitor, a 140,000 people survey on how ‘people around the world think and feel about science and major health challenges’. Among the many interesting pieces of information, not surprisingly, attitudes towards vaccinations are starting to be widely discussed in the press.Continue reading “Vaccine hesitancy is not correlated with social media penetration at country-level in Europe”
Online misinformation, fake news, false news, hoaxes, you name it, has been blamed for almost everything bad happening in the last years, from the success of Trump to Brexit, from the election of Bolsonaro to the (relative) spread of the anti-vax movement. The scientific consensus on the prominence and on the effect of online misinformation, however, is, at best, mixed.Continue reading “Morgue employee cremated by mistake while taking a nap”
There is a joke among pilots—of course, I never heard any pilot actually saying the joke, but I found it online in plenty of commentaries about automation—according to which the best aeroplane crew is composed by a computer, a pilot, and a dog. The computer flies the plane. The pilot feeds the dog. The dog’s task is to bite the pilot whenever they try to interfere with the computer’s work. In other words: let the machine do the job for you.
Last week – April 25 – Facebook posted the 2018 first-quarter data on revenues and users (here the original post from Facebook.) The perhaps unexpected take-home message is that, in spite of the Cambridge Analytica data scandal, everything seems to go well with the social media. In particular, monthly users continued to grow at the expected rate (see the graph below – original here).
Few thoughts on an important paper that just appeared in Science, The spread of true and false news online. The paper received (and will receive) justified attention: it is massive (“~126,000 rumor cascades spread by ~3 million people more than 4.5 million times” in a long temporal window – from 2006 to 2017), it includes several detailed analyses (the authors did not only check basic metrics such as speed and size of diffusion, but they measured things like structural virality; the proportion of political versus non-political news; the role of bots; they run a sentiment analysis of the tweets, etc.), and it has a straightforward (and I guess welcome to many) take-home message: “fake” news are more successfull than “true” news in social media, at least in Twitter (*).