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 terms that may carry a positive or negative connotation beyond their literal meaning.
The term 'bitch' in the context of the tweet is derogatory and biased against women.
Replace the term with 'person' or 'individual' to maintain neutrality.
The use of exciting or shocking stories or language at the expense of accuracy, in order to provoke public interest or excitement.
The description of the ex's dance as 'pretty sensually' is sensationalist and may not be necessary for the factual reporting of the event.
Describe the event without using subjective or sensationalist language.
Leaving out important details that could give a more complete picture of the situation.
The article does not provide information on the nature of the backlash SiR received, which could help readers understand the severity and scope of the public reaction.
Include details about the backlash, such as the number of people involved or the nature of their complaints.
- 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.