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.
Exaggerating or sensationalizing aspects of a story to attract attention.
The use of phrases like 'I swear to God I’ll smack your phone or camera out of your hand' and 'anyone who crosses their boundaries would regret it' adds a sensational tone to the article.
Rephrase the statements to focus on the importance of respecting the family's privacy without using aggressive language.
Provide a balanced view by including perspectives from bloggers or TikTokers on how they plan to respect the event.
Using emotional language to influence the audience's feelings.
The article includes emotional language such as 'You must show respect to the family' and 'If you do too much, don’t try me,' which appeals to the reader's emotions.
Use neutral language to convey the message about respecting the family's privacy.
Include factual information about the funeral arrangements and any guidelines provided by the family.
- 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.