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.
Biased language
Using language that is partial or expresses prejudice.
Terms like 'simp', 'useless Twitch 304', and 'drones' are emotionally charged and convey a negative bias towards the subjects.
Suggested Changes
Use neutral language to describe viewers and individuals involved in the controversy.
Sensationalism
The use of exciting or shocking stories or language at the expense of accuracy, in order to provoke public interest or excitement.
The article's title and content use sensational language such as 'claps back' and 'lashed out' to dramatize the conflict.
Rephrase the title to something more neutral, such as 'xQc responds to Fresh & Fit's remarks on Pokimane's Twitch departure'.
Avoid using dramatic language that exaggerates the nature of the interactions.
Unsubstantiated claims
Claims made without evidence to support them.
The article quotes Myron Gaines without providing evidence for his claims about 'men waking up' and 'the tide turning'.
Provide evidence or context for Gaines' claims, or indicate that these are his opinions rather than facts.
- 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.