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.
Sensationalism
Use of sensational language to create a buzz or emotional reaction.
The title 'This Is Embarrassing' Selena Gomez Sends Internet Into A Frenzy As She Mistakes K-Pop Fan Base For Her Own' uses sensational language to describe the event.
Suggested Changes
Use a more neutral title such as 'Selena Gomez Mistakenly Shares K-Pop Group's Fan Photo, Prompting Light-Hearted Reactions Online'
Biased language
Language that is partial or prejudiced towards one side.
The use of the word 'embarrassing' in the title and the article implies a negative judgment of Selena Gomez's actions.
Replace 'embarrassing' with 'unintentional' or 'accidental' to maintain a neutral tone
- 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.