A shakeup in Ukraine's SSSCIP, and turmoil at OpenAI.
- Bias Rating
10% Center
- Reliability
80% ReliableGood
- Policy Leaning
10% Center
- Politician Portrayal
32% Negative
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By creating an account, you agree to our Terms and Privacy Policy, and subscribe to email updates. Already a member: Log inBias Score Analysis
The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.
Sentiments
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- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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Contributing sentiments towards policy:
70% : An investigation revealed that workers dealing with user reports on dating apps struggle with "unattainable" expectations and traumatic content.58% : Continue reading "New Educational Guidelines Developed to Bring Trusted Computing to Billions of Devices"EU cybersecurity exercise: foster cooperation, secure free and fair EU elections (Parlamento Europeu) To evaluate and strengthen current working methods ahead of the 2024 elections, EU institutions have organised a cybersecurity exercise today.
48% : Indian Hack-for-Hire Group Targeted U.S., China, and More for Over 10 Years (The Hacker News) Indian Hack-for-Hire Group targeted U.S., China, Pakistan, and more for over a decade.Malicious Apps Disguised as Banks and Government Agencies Targeting Indian Android Users (The Hacker News)
47% : A data breach at a local council has disrupted work, but the ICO and government are satisfied with the remediation measures.
44% : Researchers used machine learning to analyze Hungarian media reports and found Russian narratives soured the nation's perspective on EU sanctions and arms deliveries months before the Ukraine invasion.
*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.