Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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CNN
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 shocking or exciting language at the expense of accuracy, in order to provoke public interest.
The title 'These are your own words!' CNN reporter grills GOP candidate over 'execute Obama' posts' uses sensational language to attract attention.
Use a more neutral title such as 'CNN reporter questions GOP candidate on previous social media remarks'
Language that is partial or prejudiced towards particular views or groups.
Phrases like 'far-right', 'controversial remarks', and 'promoted QAnon conspiracy theories' carry a negative connotation and suggest bias.
Replace with neutral descriptors such as 'right-leaning' or 'made remarks that have sparked debate'
Presenting one side of a story more favorably than the other.
The article focuses heavily on the controversial aspects of Michele Morrow's candidacy and statements, with less attention to her platform or responses to the questions posed.
Include more information about Morrow's platform and policies, and provide a balanced view of the interview
Claims that are presented without evidence or support.
The article mentions 'Morrow, a homeschooling advocate who defeated the Republican incumbent for the nomination in a surprise upset', without providing evidence for the 'surprise upset'.
Provide data or sources to support the claim of a 'surprise upset'
- 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.