News Shaman aims to highlight the emotional impact and rhythmic flow of reading a collection of news stories. Its first version is an editorial tool that offers a quick view of the emotional analytics of a given story or list of stories. This allows a publisher to gauge whether their feature series or newsletter digest is setting an emotional tone that fits their readers, and begin to iterate on the best flow for their content; is it better to open with a downer and finish with an inspiring glimmer of hope, or start irreverent and end with a sober reflection? Combined with analytics tools, News Shaman can begin to answer these questions, and help gain editorial insight into how readers are reading and reacting to stories.
This project was built by Liam Andrew, Kathryn Beaty, and Ben Hasson at The Huffington Post and Change.org Editors Lab hackathon in NYC on April 8-9, 2016. Code is available on GitHub.