Martha Stewart, 82, insists: ‘I pretty much look the same as when I was 17’.

[ 24/10/2023 18:49 ] Read on metro.co.uk

Report Overview: The article contains some manipulations such as sensationalism, biased language, and appeal to authority. However, the overall score is relatively high as the majority of the content is objective.

Sides Objectivity Scores

Martha Stewart (90)

Sides Representation Balance

Favored Side

Martha Stewart

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Detected Manipulations & Suggested Changes

Sensationalism

Presenting information in a way that is intended to provoke excitement, shock, or interest.

The article uses sensationalism by emphasizing Martha Stewart's age (82) and her claim that she looks the same as when she was 17. This is done to create intrigue and capture the reader's attention.

Present the information in a more neutral tone without exaggerating or sensationalizing Martha Stewart's age or appearance.

Biased language

Using language that favors one side or perspective over another.

The article uses biased language by referring to Martha Stewart as an 'octogenarian' and describing her as 'driving fans crazy' with her photoshoots. This language can create a negative or dismissive tone towards her.

Use neutral language when describing Martha Stewart's age and activities to avoid bias.

Appeal to authority

Using the opinion or endorsement of an authority figure to support a claim or argument.

The article uses an appeal to authority by mentioning that Martha Stewart became the oldest person in history to feature on the cover of Sports Illustrated’s annual swimsuit issue. This is used to support the idea that she is still relevant and attractive.

Provide additional evidence or perspectives to support the claim that Martha Stewart is still relevant and attractive, rather than relying solely on her appearance on the magazine cover.

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- 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.