List of Best News APIs in 2025
Learn about the top 10 news APIs and what to look for when choosing the right news API for your business.
In an increasingly polarized media landscape, political bias in news coverage is no longer an exception, it’s the norm. Whether subtle or overt, the ideological leanings of news sources influence how stories are framed, what details are emphasized, and which voices are amplified. For organizations relying on accurate, balanced, and diverse information, recognizing and accounting for this bias is more critical than ever.
At Webz.io, we understand that our customers need more than just access to massive volumes of news data, they need the tools to navigate and analyze it effectively. That’s why we’re excited to announce the launch of our latest feature: political bias detection.
Our new trust.bias attribute adds a powerful filter to the Webz.io News API,
allowing you to segment and analyze news content based on its political orientation. Whether you’re building media monitoring dashboards, researching public sentiment, or analyzing misinformation trends, this feature gives you an extra layer of control and precision.
The trust.bias attribute includes three values:
By integrating this functionality, we provide more control and transparency over the data your solution relies on to generate accurate insights.
Our customers serve a range of industries, each with unique challenges in navigating misinformation and biased reporting. Here’s how they’ve told us they plan to use these new trust categories:
Biased reporting can shape public perception, influence political stability, and distort how events are interpreted across regions or sectors. By accounting for political bias, providers ensure that their insights are balanced, context-aware, and capable of identifying emerging risks driven by ideological narratives or misinformation.
Political coverage often drives public discourse, influences brand perception, and reflects societal divides. Understanding the political lean of news content enables these companies to deliver deeper insights into media narratives, track sentiment across ideological lines, and help clients respond strategically to reputational or policy-related risks.
In industries like finance, political bias in reporting can sway market perceptions or public policy discussions. Filtering news coverage by bias enables firms to assess how different political sides are framing regulatory changes or corporate activities, which is critical for anticipating risk.
You can immediately start using Trust Bias tags by adding the trust.bias filter to your API queries. Check our documentation for implementation details.
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!
Learn about the top 10 news APIs and what to look for when choosing the right news API for your business.
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 […]
In an increasingly polarized media landscape, political bias in news coverage is no longer an exception, it’s the norm. Whether subtle or overt, the ideological leanings of news sources influence how stories are framed, what details are emphasized, and which voices are amplified. For organizations relying on accurate, balanced, and diverse information, recognizing and accounting […]