Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Palestinians
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 emotionally charged terms that favor one side.
The term 'martyred' is used repeatedly, which is a loaded term that implies a particular perspective on the conflict.
Use neutral terms such as 'killed' instead of 'martyred' to maintain objectivity.
Leaving out important context or perspectives.
The article does not provide any context or perspective from the Israeli side, such as reasons for the shelling or any statements from Israeli officials.
Include statements or perspectives from the Israeli side to provide a more balanced view of the events.
Disproportionate focus on one side of the story.
The article focuses almost exclusively on the Palestinian casualties and injuries without mentioning any Israeli casualties or the broader context of the conflict.
Provide information on both sides of the conflict, including any Israeli casualties or damage, to ensure balanced reporting.
- 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.