Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Celine Dion
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 attract attention.
Phrases like 'stunned viewers all over the world' and 'an estimated one billion people watched' are examples of sensationalism. These statements are designed to create a dramatic effect.
Replace 'stunned viewers all over the world' with 'impressed many viewers'.
Replace 'an estimated one billion people watched' with 'a large global audience watched'.
Using emotional language to elicit an emotional response from the audience.
The article uses phrases like 'sparkled in a beaded gown' and 'supreme honour' to evoke an emotional response from the reader.
Replace 'sparkled in a beaded gown' with 'wore a beaded gown'.
Replace 'supreme honour' with 'great honor'.
- 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.