Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Taylor Swift
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 create excitement and interest.
NBC lean into Taylor Swift's upcoming MetLife visit by using her 'Welcome To New York' song in their teaser clip for Chiefs-Jets... with broadcaster set to enjoy biggest TV audience of the YEAR for Sunday night primetime game
Use neutral language to describe the event without exaggeration.
The article selectively focuses on certain information to support a particular narrative.
The game is expected to draw a massive audience after last week's contest drew 24.3 million viewers - the highest total of the week.
Provide a more comprehensive view of the audience numbers by including data from other games or time periods.
The article uses language that favors a particular side or viewpoint.
NBC have leaned into the Taylor Swift-Travis Kelce hype
Use neutral language to describe the relationship between Taylor Swift and Travis Kelce.
- 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.