Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Mika Zibanejad
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.
Making assumptions or predictions without firm evidence.
The article states, 'Between Sullivan’s Sweden visit and the purchase of a new home in New York, it sure seems like Zibanejad will be a Ranger on Opening Night of the 2025-26 season.' This is speculative as it assumes future events based on current actions without concrete evidence.
Avoid making assumptions about future events without concrete evidence.
Present the facts without suggesting outcomes that are not confirmed.
Using emotional language to influence the reader's perception.
Irma Zibanejad's quotes about the rumors being 'taken out of the air' and 'zero truth' appeal to the reader's sense of injustice and sympathy.
Present Irma Zibanejad's statements in a factual manner without emotional language.
Focus on the factual content of her statements rather than the emotional tone.
- 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.