Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
HonestyMeter - AI powered bias detection
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Chrissy Teigen
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 language that unfairly favors one side over another.
The article refers to online commenters as 'dorks' and 'miserable', which reflects a negative bias towards them.
Use neutral language to describe online commenters, such as 'individuals' or 'commenters'.
Avoid using derogatory terms that may influence the reader's perception.
Using emotional language to sway the audience's feelings.
Chrissy Teigen's statements are described as a 'rant', which may evoke sympathy for her and disdain for the commenters.
Present Chrissy Teigen's statements as 'responses' or 'comments' rather than a 'rant'.
Focus on the content of her statements without emotionally charged descriptors.
- 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.