Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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US Administration
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 dramatic language to provoke interest or excitement at the expense of accuracy.
The article uses dramatic language such as 'devastating and tragic milestone' and 'existed in fear for their lives' which may sensationalize the situation.
Use neutral language to describe the situation without adding emotional weight.
Language that is partial or prejudiced towards one side or another.
The article uses phrases like 'terrorist group attacked Israel' and 'unprecedented attacks on Israel', which could imply a bias against Hamas.
Use neutral terms such as 'militant group' instead of 'terrorist group' to describe Hamas.
Leaving out important details that could change the perception of the story.
The article does not provide information on the circumstances of the hostages' capture or the perspective of Hamas, which could be key to understanding the full context.
Include information on the circumstances of the hostages' capture and any statements or perspectives from Hamas.
- 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.