Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Victim
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 use of shocking or exciting language to provoke public interest.
The headline uses the word 'friendly' to describe the victim, which adds an emotional layer to the story and may influence readers' perceptions.
Use a more neutral headline such as 'Man Charged with Murder of 62-Year-Old Woman in Leeds'.
Language that unfairly favors one side over another.
The article includes quotes from neighbors that describe the victim in a positive light, which may create sympathy for her and bias against the accused.
Include more factual information about the incident and the investigation without focusing on personal anecdotes.
- 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.