Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Survivors and Critics
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.
The use of shocking or exciting language to provoke public interest.
The article uses phrases like 'horrifying cult massacre' and 'tragically lost a staggering 11 family members' to evoke strong emotions.
Use more neutral language to describe the events, such as 'tragic event' instead of 'horrifying cult massacre'.
Language that unfairly favors one side over another.
The article describes the tourism venture as 'a money grab' and 'capitalise on a tragedy', which reflects a negative bias.
Present the tourism venture's perspective more neutrally, such as stating their goals without judgmental language.
Giving more weight to one side of an argument than the other.
The article gives more space to the criticisms of the tourism venture than to the explanations provided by the company owner.
Include more detailed explanations from the tourism venture about their intentions and how they plan to address concerns.
- 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.