Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
HonestyMeter - AI powered bias detection
CLICK ANY SECTION TO GIVE FEEDBACK, IMPROVE THE REPORT, SHAPE A FAIRER WORLD!
Daily Star
Caution! Due to inherent human biases, it may seem that reports on articles aligning with our views are crafted by opponents. Conversely, reports about articles that contradict our beliefs might seem to be authored by allies. However, such perceptions are likely to be incorrect. These impressions can be caused by the fact that in both scenarios, articles are subjected to critical evaluation. This report is the product of an AI model that is significantly less biased than human analyses and has been explicitly instructed to strictly maintain 100% neutrality.
Nevertheless, HonestyMeter is in the experimental stage and is continuously improving through user feedback. If the report seems inaccurate, we encourage you to submit feedback , helping us enhance the accuracy and reliability of HonestyMeter and contributing to media transparency.
Exaggerating or sensationalizing details to attract attention.
The headline 'Martin Kemp rushed to hospital after gruesome chainsaw accident' is sensationalized to attract readers.
Provide a more factual headline, such as 'Martin Kemp experiences chainsaw accident, receives medical attention.'
Using sensationalized headlines or content to attract clicks.
The article includes multiple calls to action to follow the Daily Star on various platforms, which detracts from the main story.
Focus on providing more details about the incident and less on promoting the news outlet.
Leaving out important details that would provide a fuller understanding of the situation.
The article lacks details about the severity of the injury and the current condition of Martin Kemp.
Include more information about Martin Kemp's condition and any medical treatment he received.
- This is an EXPERIMENTAL DEMO version that is not intended to be used for any other purpose than to showcase the technology's potential. We are in the process of developing more sophisticated algorithms to significantly enhance the reliability and consistency of evaluations. Nevertheless, even in its current state, HonestyMeter frequently offers valuable insights that are challenging for humans to detect.