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.
The article uses biased language that favors the Palestinians and portrays Israel in a negative light.
The article refers to Israel's actions as 'cutting off food and water for Gaza' and 'heavily bombarding Gaza with air strikes,' which creates a negative perception of Israel's actions.
Use neutral language to describe the actions of both sides.
The article omits key information that could provide a more balanced perspective.
The article does not mention the reasons behind Israel's actions or the attacks by Hamas that led to the conflict.
Include information about the attacks by Hamas and the reasons behind Israel's actions.
The article relies heavily on quotes from Barack Obama to support its claims.
The article quotes Obama multiple times to support the argument that Israel's actions could backfire and harm Palestinian attitudes.
Include a variety of perspectives and sources to provide a more balanced view.
- 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.