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.
Use of exciting or shocking stories at the expense of accuracy, to provoke public interest or excitement.
The title 'Going to Smack the Sh*t Out of His A**' suggests a physical altercation which is misleading and sensational.
Use a more accurate and less provocative title, such as 'Shaquille O'Neal Teases Charles Barkley Over Illness in Good Humor'.
Headlines that do not accurately reflect the content of the article.
The headline implies a violent intent by Shaquille O'Neal towards Charles Barkley, which is not supported by the content of the article.
Change the headline to accurately reflect the playful banter between the two, avoiding any suggestion of actual violence.
Attempting to manipulate an emotional response in place of a valid or compelling argument.
The article plays up the entertainment aspect and the humor in the situation to engage the reader's emotions.
Provide a more balanced view of the situation without emphasizing the emotional aspect of the banter.
- 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.