Media Manipulation and Bias Detection
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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.
Exaggerating or sensationalizing events to attract attention.
The article uses phrases like 'stunning display' and 'shock trade' to describe Luka Doncic's performance and trade, which may exaggerate the events.
Use more neutral language to describe Luka Doncic's performance, such as 'impressive' instead of 'stunning'.
Avoid using terms like 'shock trade' and instead describe the trade as unexpected or surprising.
Using language that unfairly favors one side over another.
The article describes Mahomes' reaction to Doncic's trade as 'stunned' and 'sick', which may imply a negative bias towards the trade.
Present Mahomes' reaction in a more neutral manner, such as 'Mahomes expressed surprise and disappointment at the trade.'
- 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.