Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Selena Gomez
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.
Using emotional language to sway the audience's feelings.
The article describes Selena Gomez as 'sobbing' and 'distraught,' which emphasizes her emotional state rather than focusing on the factual content of her message.
Focus on the content of Gomez's message rather than her emotional state.
Provide more context on the policies she is criticizing.
Using language that unfairly favors one side over another.
The article uses terms like 'crocodile tears' and 'unwell person' to describe Gomez, which are derogatory and biased.
Use neutral language when describing both sides.
Avoid using derogatory terms and focus on the arguments presented.
Giving unequal weight to different perspectives.
The article provides more detailed coverage of Gomez's emotional response compared to the factual responses from Trump and his supporters.
Provide more balanced coverage by including more factual information from both sides.
Ensure equal representation of both perspectives.
- 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.