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.
The article uses sensational language to describe Selena Gomez's reaction to Lionel Messi's performance.
The article describes Selena Gomez as 'gobsmacked' and 'visibly stunned' by Messi's performance.
Use neutral language to describe Selena Gomez's reaction.
The article uses biased language to favor Selena Gomez over Lionel Messi.
The article refers to Selena Gomez as an 'A-List megastar' and 'leading light', while Messi is only described as a 'World Cup winner' and 'legendary winger'.
Use neutral language to describe both Selena Gomez and Lionel Messi.
The article mentions the presence of other celebrities and Prince Harry to add credibility to Selena Gomez's opinion of Lionel Messi.
The article mentions that Leonardo DiCaprio, Owen Wilson, and Prince Harry were also present at the game.
Remove the mention of other celebrities and Prince Harry as it is irrelevant to Selena Gomez's opinion of Lionel Messi.
- 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.