News Quality Scoring Project: Surfacing Great Journalism

The News Quality Scoring (NQS) uses artificial intelligence and machine learning to surface great journalism from the web. 

 

The Problem

The legitimate news media is in a prolonged crisis, with newsrooms disappearing, revenues (and resources for reporting) drying up, with no clear path ahead to a sustainable business model for quality journalism. Online, a deeply investigated story that cost hundreds of thousands of dollars has the same dollars-per-page view value as a cut-and-paste listicle, and advertisers have no incentive to distinguish between good journalism and schlock — eyeballs are eyeballs.

The Solution

The News Quality Scoring Project seeks to change this equation and correct the chronic undervaluation of quality journalism. The organization is developing a machine learning algorithm that rates news stories on a 1-5 scale based on their journalistic merit, downgrading not just superficial reporting but also content items that bear the hallmarks of “fake news.” The idea is to differentiate “commodity news” from “value-added news” and share the information with customers — news publishers and distributors as well as advertisers. The idea is that, over time, as advertisers seek to be associated with quality product, the incentives will increasingly favor publishers that produce quality.

Stage of Development

  • Early Stage
  • Established Prototype
  • Scaling
  • Other

Organization to Receive Funds

News Quality Scoring Project

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