Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Aaron McKenna
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 aspects of a story to attract attention.
The article describes Janibek Alimkhanuly as 'the most feared world champion' and Aaron McKenna as a 'rising star' who is also 'feared'.
Provide evidence or quotes from other fighters or analysts to support the claim that Alimkhanuly is 'the most feared world champion'.
Avoid using hyperbolic language without substantiation, such as 'the most feared'.
Using emotional appeals rather than factual evidence to persuade the audience.
McKenna's statements about wanting to bring boxing back to the '80s and '90s era evoke nostalgia and emotional appeal rather than focusing on current factual analysis.
Include statistics or expert opinions on how the frequency of fights has changed over the years to provide a factual basis for McKenna's claims.
Balance emotional appeals with factual data or expert analysis.
- 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.