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.
Claims made without providing solid evidence or sources.
The article states that Kevin Costner and Jewel spent New Year's Eve together and that there is a 'very big attraction on both sides,' citing an anonymous source.
Provide evidence or confirmation from the individuals involved to substantiate the claims about their relationship.
Clearly label speculative content as unconfirmed or rumor.
Using emotional responses instead of logical arguments.
The article uses phrases like 'Kevin likes to be in a relationship, so this is cool' to evoke a positive emotional response without providing objective analysis.
Avoid subjective language and focus on factual reporting.
Using sources without revealing their identity.
The article quotes an anonymous source to provide insights into the relationship between Kevin Costner and Jewel.
Use named sources or provide context for why the source remains anonymous.
- 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.