Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Diners' Opinions
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.
Use of sensational language to provoke interest at the expense of accuracy.
The article uses phrases like 'savaged by diners' and 'up in arms about the portion sizes' which may exaggerate the negativity of the feedback.
Use neutral language to describe customer feedback.
Language that is partial or prejudiced towards particular views.
The use of phrases such as 'eye-watering £65 per person' and 'hungry fans complaining' suggests a negative bias towards the price and portion size of the roast.
Present the price and customer opinions without emotive language.
Reporting that disproportionately covers one side of an issue.
The article focuses more on the negative comments from diners than on the positive aspects of the roast or the high rating of the Savoy Grill.
Include more positive customer reviews to provide a balanced view.
Attempting to manipulate an emotional response in place of a valid or compelling argument.
Comments like 'would I have to sell a kidney to pay for it' are included to evoke an emotional response about the price rather than providing a rational analysis.
Avoid including hyperbolic statements that do not contribute to an objective discussion of the topic.
Headlines that do not accurately reflect the content of the article.
The headline suggests widespread criticism of the roast, which may not be representative of all diners' opinions.
Adjust the headline to reflect a more balanced view of the feedback.
- 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.