Ergo News is on a mission to make it easier to understand the news. With an increased awareness of misinformation, political divide, and public mistrust in the media, readers either end up sticking to one news outlet or invest valuable time in researching the story. Neither are ideal. Ergo News not only aggregates news, it also surfaces key insights and timelines to help you understand the fuller picture of today’s top events..
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 News 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 opinionated, politically influences, or sentimental the reporting is.
Here's how Ergo News highlights deeper context so you can have the full picture.
A snapshot of the publishers who are reporting on this subject. Ergo News also outlines source bias, meaning publishers who tend to report through the lense of a political ideaology. See how stories develop differently and what stories are being discussed more on the left and right sides of politics.
An aggregate of the stories being reported on a single topic. Ergo News uses tags to highlight potential elements that may influence the reader such as "opinionated language", "negative tone", and "left" or "right".
Explore relevant events or topics that influence the news you're reading today. Ergo News provides links to related, oftentimes supporting, Wikipedia pages so you have the fuller understanding of a subject.
See the trending keywords that are shaping the narrative. You can search keywords or phrases to see how they've been reported over time.
The Ergo News database independently pulls from dozens of news sources reporting thousands of articles daily. Ergo News has over 2 million articles dating back to March of 2020. We continue to add sources to our database and welcome requests for specific publishers.
Ergo News works with Media Bias / Fact Check, an independent website that has promoted awareness of media bias and misinformation by rating the bias, factual accuracy, and credibility of media sources, large and small.
Ergo News 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 News uses natural language processing to detect words and phrases in context that suggest an opinion. The article may also contain facts, but opinions are also expressed in the article. At this time Ergo News does not distinguish an article that states opinions from an article sourced from an opinion section of a publication.
Ergo News analyzes the title and description of an article to identify phrases, names, or events that support the content of the article. We pull the Wikipedia pages for these words, names or events to provide relevant context.
"Polarized" means the language in the title and description skew either heavily negative or heavily positive. Understanding the tone and positioning of an article may help readers to spot language that is shaping their perception of the subjectmatter.
We welcome feedback. Please email us at hello@newsergo News.com.
Concerned by the implications and threat of misinformation, Ergo News 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 outside funding. We do not sell any personal data or run ads. We intend to keep this platform free to the public to help everyone stay informed.
These articles are published by sources that are known to report with a strong political ideology when interpreting an event.
Ergo News uses natural language processing to detect words and phrases that suggest the article’s overall tone.
