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 dramatic language to attract attention.
The title 'Monsoon Mayhem' and phrases like 'claimed the lives' and 'battered Himachal Pradesh' are examples of sensational language.
Use more neutral language such as 'Monsoon Impact in Himachal: 298 Dead Since June, Roads Blocked, More Rain Forecasted'.
Replace 'claimed the lives' with 'resulted in the deaths of'.
Use 'affected' instead of 'battered'.
Leaving out important context or details.
The article does not provide information on the government's response or measures being taken to mitigate the impact of the monsoon.
Include statements or plans from government officials on how they are addressing the situation.
Provide information on relief efforts or future plans to prevent such incidents.
- 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.