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Support Alexa Aviles for Congress · ranked by shared content topics & relevance
73match
andyogles.com
Andy Ogles for Congress
2 shared topicspolitics
72match
herbjonesforvirginia.com
Herb Jones for Congress
2 shared topicspolitics
71match
sheilaforcongress.com
Sheila For Congress
2 shared topicspolitics
71match
koh4ma.com
Dan Koh for Congress
2 shared topicspolitics
70match
mac4sc.com
Mac Deford for Congress
2 shared topicselections
70match
susieleeforcongress.com
Susie Lee for Congress
2 shared topicselections
70match
m4mi.com
Matt Maasdam for Congress
2 shared topicselections
70match
maasdam4mi.com
Matt Maasdam for Congress
2 shared topicselections
70match
bb-4mi.com
Bridget Brink for Congress
2 shared topicspolitics
69match
caitlin4tx.com
Caitlin Rourk for Congress
2 shared topicspolitics
69match
caitlinrourk.com
Caitlin Rourk for Congress
2 shared topicspolitics
69match
dixie4tn.com
Vincent Dixie for Congress
2 shared topicspolitics
69match
dm4mi.com
Donavan McKinney for Congress
2 shared topicspolitics
69match
annagolladay.com
Home - Golladay for Congress
2 shared topicspolitics
69match
susheelaforcongress.com
Susheela Jayapal for Congress
2 shared topicspolitics
69match
cammieforcongress.com
Homepage - Cammie For Congress
2 shared topicspolitics
69match
isiahforcongress.com
Isiah for Congress 2020 | NY-9
2 shared topicspolitics
69match
beaforcongress.com
HOME | Bea Valenti for Congress
2 shared topicselections

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.