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Fake vs. Trusted News: A More Precise and Flexible Approach to Classifying and Filtering Trust-Based Content

Fake vs. Trusted News: A More Precise and Flexible Approach to Classifying and Filtering Trust-Based Content

Fake vs. Trusted News: A More Precise and Flexible Approach to Classifying and Filtering Trust-Based Content

In an era of misinformation, deepfakes, and sensational headlines, not all news is created equal. The digital news landscape today is crowded with questionable sources sites that blur the lines between satire and misinformation or intentionally spread false narratives for clicks, influence, or financial gain. For companies that rely on accurate media data, distinguishing between fake and trusted news isn’t just important, it’s essential.

At Webz.io, we’re committed to helping our users cut through the noise and focus on high-quality, reliable content. That’s why we’re excited to introduce a powerful new feature: Trusted News detection, now available in our News API.

In our blog post from February 25, 2025, Webz introduced new Trust tags for Fake and Satirical news. As part of Webz’s ongoing commitment to enhancing the reliability and quality of our news data, we’ve expanded our detection mechanisms and source list to improve fake news identification, and we’ve also added a new ‘Trusted News‘ tag to highlight credible sources.


What’s new?

The new trust.category:trusted_news tag is designed to help users filter and access news articles sourced from websites identified as credible and trustworthy. This capability gives users greater control over their data pipelines and helps ensure that insights are built on a foundation of reliable information.

Webz.io continuously evaluates news domains based on editorial standards, historical accuracy, fact-checking transparency, and third-party credibility assessments.
Based on this evaluation, domains tagged as trusted_news can now be used as a filter in your API queries.

The trust.category:trusted_news attribute is added to the existing values:

  • trust.category:fake_news – Target articles originating from domains labeled as fake.
  • trust.category:satirical_news – Filter content from domains identified as satirical.


    For example: Looking to filter articles tagged as trusted news?
    Apply
    trust.category:trusted_news to your query


Why this matters for risk and media intelligence gathering

Our customers serve a range of industries, each with unique challenges in navigating misinformation reporting. Here’s how they’ve told us they plan to use these new trust categories:

Risk intelligence software providers

Filtering trusted news enables risk intelligence software providers to offer higher-quality, actionable insights, reducing risk, enhancing decision-making, and ensuring that their clients have access to the most reliable information possible.

Media intelligence software companies

Trusted news is essential to delivering more accurate, reliable, and actionable insights, which leads to better decision-making, stronger brand protection, and a competitive edge in the market.

Financial monitoring software providers

Trusted news is key to delivering accurate market intelligence, ensuring regulatory compliance, enhancing sentiment analysis, and providing reliable decision support to clients. This ability ensures that financial data remains trustworthy, allowing providers to maintain client trust and protect against misinformation-driven risks.

How to get started

For existing customers

You can immediately start using Trusted News tags by adding the trust.category:trusted_news filter to your API queries. Check our documentation for implementation details.

Not a customer yet?

If you’re looking for data you can trust to drive reliable insights, get in touch with us for a demo. Our dedicated data expert team is ready to help you get started and optimize our data for your specific use case.

The introduction of Trust Tags marks a significant step in our mission to help intelligence solution providers get the data they need to deliver reliable insights, amid the growing threat of misinformation, biased reporting, and fake news – at scale. Stay tuned as we expand our Trust field with more classifications in the coming months!

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