Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
HonestyMeter - AI powered bias detection
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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.
The article uses sensational language to grab attention and create excitement.
The article states that Donald Trump gets McDonald's delivered to court during his civil fraud trial. This statement is sensationalized to create interest.
Change the headline to a more neutral tone.
The article uses biased language that favors Donald Trump.
The article refers to Donald Trump as the 'former president' and mentions his love for McDonald's and KFC. This language portrays him in a positive light.
Use neutral language when referring to Donald Trump.
The article omits important details about the civil fraud trial.
The article does not provide any information about the specific allegations against Donald Trump or the evidence presented in the trial.
Include relevant details about the civil fraud trial and the allegations against Donald Trump.
- 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.