Media Manipulation and Bias Detection
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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.
Presenting information in a way that is intended to provoke strong emotions or excitement.
The article uses sensational language to describe the game as a 'revenge win' and highlights the high number of viewers as the 'MOST in over 25 years for MNF'.
Use neutral language to describe the game and viewership numbers.
Provide context for the significance of the viewership numbers compared to other games.
Using headlines that are intentionally deceptive or do not accurately represent the content of the article.
The headline suggests that Taylor Swift not cheering on Travis Kelce had an impact on the viewership numbers, but this is not supported by the content of the article.
Use a headline that accurately reflects the content of the article.
Avoid making unsupported claims in the headline.
Selectively choosing data that supports a particular viewpoint while ignoring contradictory data.
The article highlights the viewership numbers for the Chiefs-Eagles game but does not provide comparable numbers for other games or provide context for the significance of these numbers.
Provide comparable viewership numbers for other games to provide context.
Include information about the overall viewership trends for Monday Night Football.
Leaving out important details or facts that may significantly impact the interpretation of the information presented.
The article does not mention any other factors that may have contributed to the high viewership numbers, such as the popularity of the teams or the significance of the game.
Include information about other factors that may have contributed to the high viewership numbers.
Provide context for the significance of the game in relation to the teams' performance or standings.
Using language that favors one side or viewpoint over others.
The article refers to the Eagles' win as a 'revenge win' without providing any context for this characterization.
Use neutral language to describe the outcome of the game.
Avoid using language that implies a particular motive or intention.
- 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.