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.
The article uses sensational language to describe the controversy surrounding Matt Rife's joke about domestic violence.
Rife's joke drew a number of critics on Twitter, many of whom said they were satisfied to see the TikTok sensation in hot water.
Use neutral language to describe the controversy without adding unnecessary drama.
The article uses biased language to describe Matt Rife's response to the criticism.
Comedian Matt Rife on Monday responded after he was criticized on social media over a joke about domestic violence he told in his recently-released Netflix special Natural Selection.
Use neutral language to describe Matt Rife's response without implying bias.
The article includes statements that appeal to emotion to influence the reader's opinion.
One user said: 'Matt Rife opens his special with a 'if a woman could cook she wouldn’t have a black eye' joke. Really? This is your god?'
Avoid using emotional statements and focus on presenting objective information.
- 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.