Ergo is on a mission to spark meaningful conversations by way of meaningful insights in the news. Powered by technology, Ergo uses machine learning and natural language processing to group together relevant stories and break down key contextual insights to give you the full scope of what and how news is being reported.
Let’s say you’re scrolling through a platform and see a news article that you find surprising or questionable. Search for that headline within the Ergo database.
A digital fingerprint of that story is created through natural language processing and matched against hundreds of thousands of articles in the database to find stories with similar digital fingerprints.
Search results outlines all the sources and the timeline of how that story has developed. Additional context tags help you understand how reliable or how different groups are discussing a single event.
Here's how Ergo highlights deeper context
so you can have the full picture.
What: Source bias meter ranges from dark blue (very liberal) to gray (neutral) to dark red (very conservative), and highlights the political leaning of a media source.
Why: See how stories are being discussed on the left and right.
What: Tags highlight deeper insights into a story such as if a story includes opinions or if it was fact checked.
Why: Additional insights help you understand the motivations or how factual an article is.
What: Swipe left and right to see how a range of media outlets are reporting on a single event.
Why: Understanding who and how media outlets are reporting on a story will help you navigate the validity or evolution of a story.
The Ergo database pulls from the News API including 50 news sources reporting over 4,000 articles a day. Ergo has articles dating back to March of 2020.
Ergo strives to generate more transparency in the news. We understand that biases in news leads to deeper polarization while also acknowledging the challenges around establishing a truly unbiased reporting system. That is why we strive for transparency both from media sources and from our team.
Ergo collects the stories that are trending on social outlets in an effort to provide greater context and support dialogue that is happening now.
The Ergo algorithm uses sentiment analysis to learn and label language that indicates how polarized a statement is and flags those as being opinions.
We welcome feedback. Please email us at firstname.lastname@example.org.
Concerned by the implications and threat of misinformation, Ergo was started in a bedroom out of San Francisco in mid-2019. We are a small team of 5, pursuing this as a passion project without any funding.