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Barbershop

If You Like Barbershop(2002)

Based on real preference data from thousands of voters, here's what fans of Barbershop also love.

61 connections found

61 connections
Sort by
Friday After Next#1202x

Friday After Next

2002
56 voters
Next Friday#2171x

Next Friday

2000
56 voters
Big Momma's House#3138x

Big Momma's House

2000
50 voters
Boyz n the Hood#497x

Boyz n the Hood

1991
53 voters
Friday#591x

Friday

1995
75 voters
Coming to America#683x

Coming to America

1988
50 voters
White Chicks#752x

White Chicks

2004
58 voters
The Waterboy#839x

The Waterboy

1998
50 voters
Big Daddy#938x

Big Daddy

1999
51 voters
Harold & Kumar Go to White Castle#1035x

Harold & Kumar Go to White Castle

2004
57 voters
Happy Gilmore#1132x

Happy Gilmore

1996
55 voters
We're the Millers#1227x

We're the Millers

2013
50 voters
Freaky Friday#1326x

Freaky Friday

2003
50 voters
Night at the Museum#1424x

Night at the Museum

2006
54 voters
Knocked Up#1524x

Knocked Up

2007
51 voters
21 Jump Street#1623x

21 Jump Street

2012
61 voters
Step Brothers#1722x

Step Brothers

2008
56 voters
Pineapple Express#1819x

Pineapple Express

2008
Thriller
56 voters
Hancock#1919x

Hancock

2008
52 voters
Men in Black II#2016x

Men in Black II

2002
51 voters
Home Alone#2115x

Home Alone

1990
60 voters
Superbad#2214x

Superbad

2007
61 voters
Kick-Ass#2313x

Kick-Ass

2010
54 voters
Mean Girls#2413x

Mean Girls

2004
62 voters
Despicable Me#2513x

Despicable Me

2010
51 voters
Beetlejuice#2613x

Beetlejuice

1988
50 voters
Spider-Man#2712x

Spider-Man

2002
Action
54 voters
I, Robot#2812x

I, Robot

2004
Sci-FiThriller
51 voters
Back to the Future Part II#2912x

Back to the Future Part II

1989
50 voters
The Hangover#3011x

The Hangover

2009
66 voters
10 Things I Hate About You#3111x

10 Things I Hate About You

1999
51 voters
I Am Legend#3211x

I Am Legend

2007
59 voters
Men in Black#3311x

Men in Black

1997
Action
63 voters
The Incredibles#3411x

The Incredibles

2004
Action
59 voters
Shrek#3511x

Shrek

2001
66 voters
Easy A#3611x

Easy A

2010
50 voters
Iron Man 2#3711x

Iron Man 2

2010
Action
56 voters
Harry Potter and the Goblet of Fire#3811x

Harry Potter and the Goblet of Fire

2005
56 voters
Harry Potter and the Chamber of Secrets#3910x

Harry Potter and the Chamber of Secrets

2002
57 voters
Finding Nemo#4010x

Finding Nemo

2003
52 voters
Toy Story#4110x

Toy Story

1995
Sci-Fi
51 voters
Harry Potter and the Half-Blood Prince#4210x

Harry Potter and the Half-Blood Prince

2009
Action
52 voters
Harry Potter and the Prisoner of Azkaban#4310x

Harry Potter and the Prisoner of Azkaban

2004
ActionThriller
58 voters
Harry Potter and the Order of the Phoenix#4410x

Harry Potter and the Order of the Phoenix

2007
ActionFantasy
53 voters
Juno#459.7x

Juno

2007
50 voters
The Breakfast Club#469.4x

The Breakfast Club

1985
52 voters
Monsters, Inc.#479.4x

Monsters, Inc.

2001
61 voters
Edward Scissorhands#489.0x

Edward Scissorhands

1990
54 voters
Up#497.5x

Up

2009
54 voters
Avatar#507.3x

Avatar

2009
53 voters
Back to the Future#517.0x

Back to the Future

1985
58 voters
The Hunger Games#526.9x

The Hunger Games

2012
52 voters
Deadpool#536.9x

Deadpool

2016
50 voters
Iron Man#546.7x

Iron Man

2008
Action
58 voters
Guardians of the Galaxy#555.6x

Guardians of the Galaxy

2014
Action
50 voters
The Dark Knight#565.1x

The Dark Knight

2008
Action
57 voters
Forrest Gump#574.9x

Forrest Gump

1994
Action
55 voters
The Shawshank Redemption#584.6x

The Shawshank Redemption

1994
50 voters
The Matrix#594.3x

The Matrix

1999
54 voters
Inception#603.7x

Inception

2010
59 voters
Fight Club#613.4x

Fight Club

1999
Action
54 voters

How does this work?

These recommendations are based on real voting data, not algorithms. When thousands of people vote on their favorites, patterns emerge — people who love Barbershop consistently tend to also love certain other things. The "strength" score shows how much more likely fans of Barbershop are to enjoy each recommendation compared to the average person.

Unlike algorithmic recommendations, these connections come from actual human preferences. A high strength score means the connection is genuine — not just because two items share a category, but because the same people genuinely love both.