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 excitement, shock, or interest
The article uses sensational language like 'lit the streaming world on fire' and 'skyrocketing the site’s popularity to the moon' to describe the impact of the deal.
Use more neutral language to describe the impact of the deal.
Using language that favors one side or presents a subjective viewpoint
The article uses biased language by referring to xQc's audience as 'extremely engaged' and 'one of the most engaged audiences you’ll find on Twitch'.
Use more neutral language to describe xQc's audience engagement.
Leaving out important details that could provide a more complete picture
The article does not provide specific details about the incentives that pushed the deal from $70 million to $100 million.
Include information about the specific incentives that contributed to the increase in the deal's price.
- 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.