Media Manipulation and Bias Detection
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Bias report
HonestyMeter - AI powered bias detection
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Objectivity Score
High
Drake Adds Final Big As the What? Shows With Co-Headliner Lil Wayne.
Sides Objectivity Scores
Sides Representation Balance
Favored Side
Drake and Lil Wayne
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.
Detected Manipulations & Suggested Changes
Manufactured controversy
Introducing a controversial topic that is not directly related to the main content of the article.
The section discussing Drake's support for Tory Lanez seems to be an attempt to introduce a controversial angle into an otherwise straightforward article about tour dates.
Suggested Changes
Remove the section about Drake's support for Tory Lanez to maintain focus on the tour information.
If mentioning the controversy, provide a balanced view by including responses or perspectives from other involved parties.
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- 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.