Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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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 aspects of the story to attract attention.
The headline 'Miley Cyrus, Selena Gomez refused to film Disney crossover scenes together — thanks to mutual ex Nick Jonas' is sensational and implies ongoing drama.
Change the headline to 'Miley Cyrus and Selena Gomez had past tensions over Nick Jonas, says co-star.'
Using emotional language to elicit an emotional response from the audience.
Phrases like 'messy high school nonsense' and 'high school BS' are emotionally charged and detract from an objective recounting of events.
Replace 'messy high school nonsense' with 'past disagreements' and 'high school BS' with 'high school issues.'
Using language that shows a bias towards one side.
The article uses terms like 'rocky relationship' and 'puppy love' which can be seen as minimizing or trivializing the relationships.
Use neutral terms like 'relationship' and 'young love' instead of 'rocky relationship' and 'puppy love.'
- 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.