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.
Using language that implies a judgment or contains an emotional charge.
Phrases like 'Trump hosting gay weddings at Mar-a-lago is cringe af' and 'Donald Trump is hosting gay weddings at the Mar-a-Lago and people still think he's going to save America.' contain biased language that may influence the reader's perception.
Use neutral language to describe the event and the reactions to it, such as 'Trump's property hosted a same-sex wedding, which has been met with mixed reactions from various commentators.'
The use of exciting or shocking stories or language at the expense of accuracy, in order to provoke public interest or excitement.
The use of social media quotes with strong emotional language like 'cringe af' and 'ughhhh.. errr.. Nevermind...' may be seen as sensationalist, as it emphasizes the most extreme reactions.
Provide a more measured overview of the reactions without relying on extreme language from social media posts.
- 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.