Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Edurne De Gea
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.
Exaggerating or sensationalizing events to attract attention.
The article uses phrases like 'swirling rumours' and 'notorious fax machine incident' which sensationalize the events surrounding De Gea's potential transfer and Eurovision voting.
Use more neutral language such as 'rumors' instead of 'swirling rumours'.
Avoid using terms like 'notorious' unless providing specific evidence or context.
Using language that unfairly favors one side over another.
The article describes Eurovision voting as 'notorious for its political undertones' and 'so-called voting blocs', which implies a negative bias without providing evidence.
Provide evidence or examples to support claims about Eurovision voting.
Use neutral language such as 'Eurovision voting has been criticized for political influences' instead of 'notorious for its political undertones'.
- 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.