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Musings · ranked by category · tech stack · backlink co-citation
85match
makeyee.com
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hi-im-emmy.com
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75match
mariahmaison.com
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75match
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malsamaaz.com
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manaliveapparel.com
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70match
jillianstarrauthor.com
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70match
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70match
guhlitz.com
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1 co-citations2 shared tech1 shared categorypop-culture
70match
balancedactmedia.com
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70match
gentlycurious.com
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1 co-citations1 shared tech1 shared categorypop-culture
67match
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67match
bakahondo.com
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67match
dianparkinson.com
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67match
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1 co-citations2 shared tech1 shared categorypop-culture
67match
kangpuayju.com
Puay Ju's musings on life, love and anything under the sun
1 co-citations1 shared tech1 shared categorypop-culture
66match
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How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.