We utilize sophisticated Natural Language Processing (NLP) and Artificial Intelligence (AI) to parse news content for both the topics they mention and the way those topics are presented in order to quantify from the bottom up a political leaning assessment of the article / tweet / video / etc. We then roll up these content ratings to the associated Journalists (or pundit / anchor / influencer / etc.) who created them, and the associated Outlets (or channel / news influencer / etc.) who distributed them in order to quantify a general bias rating for those entities as well. These ratings are continually monitored by subject matter experts for quality and continuous improvement.

The Transparency Rating highlights any disparity between the stated position of a Journalist or Outlet and the actual political orientation discerned from our analysis of their published media content. When stated intent, or absence thereof, implies a political leaning different from the Bias Rating gleaned from our quantitative analysis, our Transparency Rating will help ensure readers can approach those entities with an improved contextual understanding of potential conflict of interest or misrepresentation.

We are consistently updating our automated data ingestion and processing pipeline to reflect up-to-date information and re-evaluate Bias & Transparency metrics. Our goal is to move ever-closer to a near real-time data repository of American news media bias analytics. We are also careful to ensure appropriate moderation and human review procedures are a consistent part of our service in order to ensure quality, and the specific timing of updates of various metrics depends on many factors that precludes us being able to provide a specific deadline.

Our bias ratings are built by a database and micro-services infrastructure that includes NLP Machine Learning coupled with Subject Matter Expert qualitative review. By building our assessments up from a ground-level mapping of specific topics mentioned in a given piece we help ensure that our ratings are never "top-down" generalizations of an enterprise that are simply applied to any content or personnel associated with that enterprise. This contributes to a rating that is backed up by consistently-updated quantifiable data with fewer chances for human opinions to intervene. That being said, the concept of political leaning and the inherent bias it reflects is a complicated and nuanced subject and can never be asserted to be "right" or "wrong." That is why our service looks to invite discussion and reporting of specific disagreements for our quality teams to review and utilize in the continuous improvement of our product.

Our goal is for authors / journalists / influencers to be fully engaged in our service, acknowledging and discussing and facilitating feedback regarding these ratings. With open communication and a vested interest in how their stated intents are being reflected in their published content, we foresee that trust in the qualitative appropriateness of our ratings will be very strong and motivated news readers will confidently utilize them in their informed digestion of American news media.

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