The Real-World Effects of ‘Fake News’

Anti-Vaccination Misinformation, Implications for Public Health, and the Fight Against COVID-19

Social media networks are rife with conspiracy theories and misinformation about the origins of and treatments for COVID-19. Misinformation is not a new phenomenon. However, the rise of social media and changes in how people obtain and consume news, have made misinformation much more infectious: fake news now spreads faster, wider and more freely than ever before.

How can we measure misinformation? What are its effects on public health? And what implications might this have for our fight against the Covid-19 pandemic, and for the role that users, social media companies and policy makers might play? We explore these important questions using a recent ‘test case’: misinformation around the Measles, Mumps and Rubella (MMR) vaccine.

We collect large volumes of detailed public health data from England and Wales, use Artificial Intelligence (AI) and Machine Learning (ML) algorithms to analyse huge numbers of social media posts on Twitter, and finally, deploy powerful statistical techniques capable of isolating and quantifying causal effects. We demonstrate that misinformation on social media can have real-world impacts on human behavior, and that those behavioral changes can lead to serious health problems. We find that over half of the fall in MMR vaccination coverage between 2012 and 2018 may be due to proliferation of misinformation.

The topic of misinformation is one of the most controversial and hotly debated in public discourse today. We believe that such debates can and should be enriched by clear and objective analysis, using rigorous and scientific techniques from economics, statistics, and data science.