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54match
kyleabellar.com
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6 co-citations7 shared tech1 shared categorysocial-networking
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circlesnetwork.org.uk 🇬🇧
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50match
grindr.com
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balentin.com
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47match
agence-horama.com
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46match
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46match
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femalepartnersincrime.com
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5 co-citations2 shared tech1 shared categorysocial-networking
45match
ivawin.com
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3 co-citations7 shared tech1 shared categorysocial-networking
45match
mariahmeetsworld.com
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4 co-citations7 shared tech1 shared categorysocial-networking
44match
hashtagmke.com
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5 co-citations8 shared tech1 shared categorysocial-networking
44match
feedpixel.com
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44match
kenkemp.com
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5 co-citations4 shared tech1 shared categorysocial-networking
44match
mamukagroups.com
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4 co-citations4 shared tech1 shared categorysocial-networking
44match
botonup.com
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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.