The science of fake news is a multidisciplinary challenge that requires understanding how the internet spreads content and how people process news. Fake news emerged as a global problem during the 2016 U.S. election, necessitating a comprehensive approach to define the problem, detect fake news in real time, and mitigate its harmful effects. This involves understanding how the internet spreads content, how people process news, and how these interact. The article reviews current knowledge and discusses two potential mitigation strategies: empowering individuals to identify fake news and intervention within platforms to reduce its attention. Collaboration between internet platforms and researchers is crucial to understanding the scale of the issue and the effectiveness of interventions. Fake news is defined as fabricated information that mimics news media but lacks editorial norms. The traditional safeguards against misinformation have failed in the internet age, leading to a need for new scientific efforts. The rise of fake news is linked to geographic polarization, homogenous social networks, and the influence of social media. The prevalence of fake news is difficult to measure, and its impact on individuals is largely unexplored. Fact checking and education are potential interventions, but their effectiveness is limited by confirmation bias and memory effects. Platform-based interventions, such as algorithmic changes and reducing bot activity, could help mitigate fake news. However, platforms' claims about their efforts are often unverifiable. There is a need for collaboration between platforms and researchers to evaluate the scope of the issue and the effectiveness of interventions. The article concludes that a multidisciplinary approach is necessary to reduce the spread of fake news and address the underlying issues.The science of fake news is a multidisciplinary challenge that requires understanding how the internet spreads content and how people process news. Fake news emerged as a global problem during the 2016 U.S. election, necessitating a comprehensive approach to define the problem, detect fake news in real time, and mitigate its harmful effects. This involves understanding how the internet spreads content, how people process news, and how these interact. The article reviews current knowledge and discusses two potential mitigation strategies: empowering individuals to identify fake news and intervention within platforms to reduce its attention. Collaboration between internet platforms and researchers is crucial to understanding the scale of the issue and the effectiveness of interventions. Fake news is defined as fabricated information that mimics news media but lacks editorial norms. The traditional safeguards against misinformation have failed in the internet age, leading to a need for new scientific efforts. The rise of fake news is linked to geographic polarization, homogenous social networks, and the influence of social media. The prevalence of fake news is difficult to measure, and its impact on individuals is largely unexplored. Fact checking and education are potential interventions, but their effectiveness is limited by confirmation bias and memory effects. Platform-based interventions, such as algorithmic changes and reducing bot activity, could help mitigate fake news. However, platforms' claims about their efforts are often unverifiable. There is a need for collaboration between platforms and researchers to evaluate the scope of the issue and the effectiveness of interventions. The article concludes that a multidisciplinary approach is necessary to reduce the spread of fake news and address the underlying issues.