Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Philadelphia 76ers
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 describe the defeat suffered by LeBron James.
LeBron James made history on Monday night as he set the minutes played mark, combined regular season and postseason, but suffered one of the most lopsided defeats of his career.
Remove the phrase 'one of the most lopsided defeats of his career' and provide more objective language to describe the defeat.
The article uses biased language to describe the Lakers' performance.
James was clearly frustrated with the loss and said that 'a lot' needed to change about the team’s performance in order to prevent another blowout like that on the road.
Use more neutral language to describe LeBron James' frustration and the team's performance.
The article fails to mention the final score of the game.
The Lakers fell to the Philadelphia 76ers, 138-94.
Include the final score of the game to provide complete information.
- 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.