Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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RSF
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.
Exaggerating or sensationalizing events to provoke public interest or excitement.
Phrases like 'epicentre of suffering' and 'trapped and terrified - shelled, starving, and without access to food, healthcare, or safety' contribute to a sensational tone.
Use more neutral language to describe the situation, focusing on facts and figures rather than emotive language.
Provide specific examples or data to support claims of suffering and deprivation.
Providing unequal coverage or emphasis on one side of a story.
The article provides more detailed information about the RSF's actions and intentions, with less focus on the Sudanese army's perspective or actions.
Include more information about the Sudanese army's actions and perspective to provide a balanced view.
Seek statements or responses from the Sudanese army or its allies to present their side of the story.
- 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.