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.
Use of hyperbolic or exaggerated language to provoke interest or excitement.
Phrases like 'Excitement is reaching a fever pitch', 'wildfire of anticipation', and 'powerhouse collaboration' contribute to a sensationalist tone.
Use more neutral language to describe the collaboration, such as 'anticipated' instead of 'wildfire of anticipation'.
Attempting to manipulate an emotional response in place of a valid or compelling argument.
The article uses phrases like 'OMG WHATTT' and 'This is gonna be MY FAVOURITE COLLAB EVER!' to evoke an emotional response from the reader.
Present fan reactions in a more balanced way, including a range of responses to the news.
- 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.