Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
HonestyMeter - AI powered bias detection
CLICK ANY SECTION TO GIVE FEEDBACK, IMPROVE THE REPORT, SHAPE A FAIRER WORLD!
None
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 sufficient evidence or sources.
The article states that 'talks have taken place with Rangers' and that 'EFL Championship trio Sunderland, Middlesbrough and Stoke are also said to be keen on signing the player' without providing specific sources or evidence for these claims.
Provide specific sources or evidence for the claims about the talks and interest from other clubs.
Include quotes or statements from involved parties to substantiate the claims.
Use of language that may imply a bias or subjective view.
The article describes Ridvan Yilmaz as 'injury-prone' which could be seen as a subjective judgment without supporting evidence.
Provide statistics or evidence to support the claim of Ridvan Yilmaz being 'injury-prone'.
Use neutral language such as 'has had injury issues in the past' if evidence is not available.
- 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.