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 attract attention.
The title 'Warriors' Steph Curry rips jersey in frustration after close loss to Lakers' uses sensational language to emphasize the emotional reaction of a player, which may not reflect the overall content of the article.
Suggested Changes
Use a more neutral title that focuses on the game's outcome, such as 'Lakers edge Warriors in double overtime thriller'.
Biased language
Language that is partial or prejudiced towards one side.
The article focuses on Curry's frustration and the Warriors' recent losses, which could imply a negative bias towards the Warriors.
Provide a balanced view by also mentioning positive aspects of the Warriors' performance or recent successes.
Unbalanced reporting
Reporting that disproportionately covers one side of an issue.
The article provides more detail on the Warriors' perspective, particularly Curry's frustration and the free throw disparity, which may suggest a lack of balance.
Include more information about the Lakers' performance and perspective to balance the reporting.
- 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.