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.
The article uses sensational language to create drama and intrigue.
The article uses phrases like 'has us worried', 'emotional turmoil', and 'playing on their emotions' to create a sense of drama and uncertainty.
Use neutral language to describe the situation without exaggeration.
The article uses biased language to favor one side over the other.
The article refers to Cardi B as a 'rap diva' and Offset as the 'Walk It Talk It' artist, which can create a positive image of Cardi B and a negative image of Offset.
Use neutral language to refer to both Cardi B and Offset.
The article tries to evoke an emotional response from the reader.
The article mentions Cardi B's emotional feelings, protecting people's feelings, and putting herself first, which can evoke sympathy and concern from the reader.
Stick to factual information without trying to manipulate the reader's emotions.
- 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.