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.
Presenting information in a way that is intended to provoke excitement, shock, or interest, often at the expense of accuracy.
The article uses sensational language to describe the upcoming issue and the introduction of Rabble as Miles Morales' arch-enemy.
Use more neutral language to describe the events and characters.
Using language that favors one side or perspective over another.
The article refers to Rabble as a 'villain' and describes her as having a 'seething hatred' towards Miles Morales.
Use neutral language to describe Rabble and her motivations.
Leaving out important details or context that could provide a more complete understanding of the topic.
The article does not provide information about the current storyline or the background of Miles Morales as Spider-Man.
Include a brief summary of the current storyline and Miles Morales' background for readers who may not be familiar with the character.
- 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.