Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Chiefs
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.
Use of superlatives or hyperbolic terms to create a buzz.
The phrase 'Bad football. There's not many other ways to describe it' uses sensationalism to emphasize the Dolphins' performance.
Replace with a more neutral assessment of the Dolphins' performance.
Language that is partial or shows a lack of neutrality.
The article uses biased language when discussing the Dolphins' performance, such as 'the Dolphins' offense looked like a shell of the version that scored 70 points'.
Use more neutral language to describe the Dolphins' offense, avoiding terms that imply a drastic reduction in quality.
Leaving out important details that could change the perception of the reported facts.
The article omits the Chiefs' weaknesses or any challenges they faced during the game, which could provide a more balanced view.
Include information about any difficulties or challenges the Chiefs faced during the game.
- 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.