Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Protestors
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 dramatizing events to attract attention.
The article describes the protests as 'surreal' and 'jarring,' focusing on the dramatic imagery of burning buildings and social media posts.
Provide a more balanced view by including factual information about the protests and their causes.
Avoid using dramatic language that sensationalizes the events.
Using language that unfairly favors one side over another.
The article uses phrases like 'corrupted mfs' and 'Nepal’s Gen Z uprising' which imply a bias towards the protestors.
Use neutral language when describing both sides of the conflict.
Avoid using derogatory terms or language that implies judgment.
Focusing more on one side of the story than the other.
The article primarily focuses on the protestors' perspective and the use of TikTok, with limited information on the government's actions or perspective.
Include more information about the government's response and perspective on the protests.
Provide a balanced view by giving equal weight to both sides of the story.
- 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.