Overtone: Misinformation based on Article DNA
The technology provides insight by looking at the qualities of the text itself, rather than tertiary metrics such as clicks and shares. It uses advances in Natural Language Processing (NLP) to create the type of data that is useful to creative, analytics and business teams at media companies and beyond.
The next step is sorting through articles based on what is in them on the paragraph level. Overtone can accurately label whether a paragraph is factual, opinionated, journalism, or potentially toxic. The work will begin with this model in the misinformation space, with the collaboration of citizens who want better control over what they see online.
The Overtone project will build ways to identify different types of misinformation based on the qualities of their text, using a new model to provide analysis paragraph by paragraph, the ‘DNA’ of an article. In a conversation with citizens, the project will create a taxonomy of potential misinformation that can be identified algorithmically.
Overtone uses advances in Artificial Intelligence (AI) to create data that powers an internet organised around qualitative signals. The solution is valuable not just in the context of misinformation, but in wide swaths of the media ecosystem that demand a new way of looking at content online.
Our products create qualitative data, which is not only intrinsic to the text, but independent and immediate too. Our tech means it’s also available at speed and scale. This data is used for content strategy and distribution by businesses such as publishers who want to better distribute their content, or ad and PR professionals who want to better understand what’s out there.