
If You Like Parallels(2015)
Based on real preference data from thousands of voters, here's what fans of Parallels also love.
42 connections found
#1201xARQ
2016
#2166xTime Lapse
2015A vizsga
2011
#4102xProject Almanac
2015
#596xThe Signal
2014
#674xExam
2010
#771xTriangle
2009
#853xCoherence
2014
#941xTranscendence
2014
#1030xElysium
2013
#1129xIn Time
2011
#1227xOblivion
2013
#1326xSnowpiercer
2014
#1422xLucy
2014
#1521xLooper
2012
#1619xSource Code
2011
#1714xEx Machina
2015
#1813xArrival
2016
#1913xEdge of Tomorrow
2014
#2012xMinority Report
2002
#2112xLimitless
2011
#2212xI, Robot
2004
#2312xThe Matrix Reloaded
2003
#2412xThe Butterfly Effect
2004
#2511xI Am Legend
2007
#2610xDoctor Strange
2016
#2710xJohn Wick
2014
#289.8xDistrict 9
2009
#297.9xThe Martian
2015
#307.0xDeadpool
2016
#317.0xInterstellar
2014
#326.6xThe Avengers
2012
#336.6xShutter Island
2010
#346.3xThe Prestige
2006
#356.2xCatch Me If You Can
2003
#365.9xThe Matrix
1999
#375.3xIron Man
2008
#385.2xDonnie Darko
2001
#395.1xInception
2010
#405.0xThe Truman Show
1998
#414.3xThe Dark Knight
2008
#423.6xFight Club
1999How 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 Parallels consistently tend to also love certain other things. The "strength" score shows how much more likely fans of Parallels 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.