Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Police
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 language that may imply bias or partiality.
The article uses terms like 'violent' and 'resort to lathi charge' which could imply a negative view of the protesters.
Provide more context on why the protest turned violent.
Include statements from protesters to explain their actions and demands.
Leaving out important details that could provide a fuller understanding of the situation.
The article does not detail the 10 key demands of the protesters, which are central to understanding the protest.
Include a list or description of the protesters' demands.
Provide background on the DNT Sangharsh Samiti and Rashtriya Pashupalak Sangh.
- 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.