Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Social Media Users
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 or excitement.
The term 'lobstrosity' and the reactions quoted from social media users are used to create a sensationalist tone.
Use more neutral language to describe the dish and the public's reaction to it.
Language that is biased or contains a partial perspective.
Phrases like 'Martha what in fresh hell' convey a negative tone and suggest a bias against Martha Stewart's culinary choice.
Provide a balanced view by including positive or neutral reactions, or by omitting overly negative language.
A headline that misrepresents the content of the article.
The headline 'A Lobstrosity': Social Media Is Losing It Over Martha Stewart's Latest Meal Posting' suggests a larger controversy or negative reaction than what is presented in the article.
Rephrase the headline to more accurately reflect the content of the article, such as 'Martha Stewart's Unique Chicken and Lobster Dish Sparks Conversation on Social Media'.
- 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.