Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
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.
Use of exciting or shocking stories at the expense of accuracy, to provoke public interest or excitement.
The headline suggests a dramatic reunion and a 'warning' from Jennifer Lopez, which is sensational and not supported by the content of the article.
Use a more accurate and less sensational headline that reflects the content of the article.
Headlines that do not accurately reflect the content of the article.
The headline implies a conflict or significant event ('Jennifer Lopez issues warning') that is not central to the article's content.
Rewrite the headline to accurately reflect the article's focus on professional collaborations and past relationships.
Selectively presenting data that supports a particular position while ignoring data that contradicts it.
The article focuses on positive aspects of the relationships and projects while omitting less favorable details or critical perspectives.
Include a balanced view of the projects and relationships, incorporating both successes and failures.
Language that is partial or prejudiced, favoring one side over another.
Phrases like 'hit Super Bowl commercial' and 'overwhelmingly positive response' suggest a bias towards positive portrayal without presenting any critical viewpoints.
Use neutral language and present a balanced view of the commercial's reception.
Claims that are not supported by evidence or sources.
Statements like 'Jennifer Lopez warns Ben Affleck is off limits' are presented without evidence of such a 'warning' being a significant issue.
Provide evidence for claims or clarify that they are opinions or interpretations.
- 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.