Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Taylor Swift
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 sensational language to evoke strong emotions.
Taylor Swift says she has a 'shattered heart' following the death of a fan who was taken to hospital before her show in Rio de Janeiro, Brazil.
Use neutral language to describe the emotional impact of the incident.
The article includes biased language that favors Taylor Swift.
In a note shared to her Instagram stories, Swift said: 'I can't believe I'm writing these words but it is with a shattered heart that I say we lost a fan earlier tonight before my show.'
Use neutral language to present Taylor Swift's statement.
The article uses emotional language to elicit sympathy for Taylor Swift.
She added: 'I feel overwhelmed by grief when I even try to talk about it. I want to say now I feel this loss deeply and my broken heart goes out to her family and friends.'
Present the emotional impact without using biased language.
- 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.