Emperor

Summary: As the Japanese surrender at the end of World War II, General Fellers is tasked with deciding if Emperor Hirohito will be hanged as a war criminal. Influencing his ruling is his quest to find Aya, an exchange student he met years ...

Release Date: July 27, 2013

Genres: Drama, History, War

Director: Peter Webber

Writers: Vera Blasi

, David Klass

, Shiro Okamoto

Runtime: 1 h 47 min

MPAA: PG-13

Production: Krasnoff Foster Productions, Envision Casting, Fellers Film

Distributor: Lionsgate, Roadside Attractions

Countries: Japan, United States, New Zealand

Language: English

Domestic: $ 3,346,265

International: $ 11,511,975

Box office:

Domestic:$3.3MInternational:$11.5MWorldwide:$14.9M

Box office International:

Source: The Numbers

Adaptation/remake:

based on true story

14%

The Rotten Tomatoes audience rated this 14% higher than the critics.

32%46%

No Metacritic ratings imported yet.

11%56%

11% of the Stars & Main Cast are Female.

56% of the Stars & Main Cast are "diverse."

Asian55.56%White44.44%

1.45

Commonsensemedia

Message3/5
Role model2/5
Violence3/5
Sex2/5
Language3/5
Drugs3/5

This film gets a 1.45/5 family friendly score

Please help improve our site and

add a Family Friendly Rating.

CONTENT BREAKDOWN

Methodology

RottenTomatoes:

32%46%

Douban:

IMDb:

Kinopoisk:

OFDb:

Methodology

Cast

Stars:

Supporting cast:

Other Cast, Production

Other cast:

Production:

Representation

Star

Supporting

Other

Production

Race	White	Mixed / Other	Asian	Black	Total	Visuals	Info
Kairos	12		1	1	14		A third party facial recognition software company we used to maintain objectivity. Upload images to the facial recognition demo page to check the veracity of our data set. Or use their API and do a bulk peer review if you'd like. Source: https://www.kairos.com/demos
Ethnic	1	1			2		This is the most reliable data source for accurate ethnic breakdowns of famous people. Often the information is crowdsourced by users and they cite all their sources (family trees, obituaries, census archives, etc.) on the bottom of the page. The only issue is converting their ambiguous and inconsistent verdicts into quantifiable variables. Source: https://ethnicelebs.com/
Surname	2				2		A third party free program that uses US Census data to create an algorithm that analyzes surnames and guesses what ethnicity the person is. Obviously there are issues with this data set such as African Americans who have the last names of their ancestors' slave owner. However, when no other data set is available, this can give a rough estimate and expand the data pool for the less important cast members with no IMDb or TMDb image. Please consider downloading their source code via GitHub to verify the accuracy of our data set, and to peer review our conclusions. Source: https://pypi.org/project/ethnicolr/
Bettaface	1				1		A third party facial recognition software company we used to maintain objectivity. Upload images to the facial recognition demo page to check the veracity of our data set. Or use their API and do a bulk peer review if you'd like. Source: https://www.betafaceapi.com/demo_old.html
Familysearch	1				1
Total	17	1	1	1	20
Cast Percentages	85%	5%	5%	5%	100%	{"name":"Cast Percentages","series":[{"name":"White","y":85,"color":"#2b908f","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":5,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Asian","y":5,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":5,"color":"#f45b5b","sliced":true,"selected":true}],"prefix":""}
U.S. Population (2020) Percentage	57.84%	9.32%	6%	12.4%		{"name":"U.S. Population (2020)","series":[{"name":"White","y":57.84,"color":"#2b908f"},{"name":"Arab","y":0.54,"color":"#DF5353"},{"name":"Asian","y":6,"color":"#90ee7e"},{"name":"Black","y":12.4,"color":"#f45b5b"},{"name":"Indian","y":1.35,"color":"#7798BF"},{"name":"Indigenous","y":1.12,"color":"#aaeeee"},{"name":"Latino","y":18.73,"color":"#eeaaee"},{"name":"Mixed \/ Other","y":9.32,"color":"#55BF3B"},{"name":"Jewish","y":2.02,"color":"#ff0066"}],"prefix":""}	Source: US Census (Note: Racial and ethnic categories overlap so the sum will not equal 100%.)
U.S. Population (2020) Representation	+27.16	-4.32	-1	-7.4		{"name":"U.S. Population (2020)","series":[["White",57.84],["Mixed \/ Other",9.32],["Asian",6],["Black",12.4]],"cast":[{"name":"White","y":85,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5,"color":"#55BF3B"},{"name":"Asian","y":5,"color":"#90ee7e"},{"name":"Black","y":5,"color":"#f45b5b"}]}
U.S. Buying Power (2023) Percentage	72.69%	1.54%	6.97%	8.02%		{"name":"U.S. Buying Power (2023)","series":[{"name":"White","y":13897000000000,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":1333100000000,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":1533100000000,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":136400000000,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":1924000000000,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":295300000000,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"}	Source: Selig Center, University of Georgia
U.S. Buying Power (2023) Representation	+12.31	+3.46	-1.97	-3.02		{"name":"U.S. Buying Power (2023)","series":[["White",72.69],["Mixed \/ Other",1.54],["Asian",6.97],["Black",8.02]],"cast":[{"name":"White","y":85,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5,"color":"#55BF3B"},{"name":"Asian","y":5,"color":"#90ee7e"},{"name":"Black","y":5,"color":"#f45b5b"}]}
U.S. Average Individual Income (2018) Percentage	65.34%	7.28%	7.52%	9.43%		{"name":"U.S. Average Individual Income (2018)","series":[{"name":"White","y":11825174998483,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":1360705388565,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":1706765993728,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":164296821776,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":1721419354421,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":1318328353188,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"}	Source: IPUMS-CPS, University of Minnesota
U.S. Average Individual Income (2018) Representation	+19.66	-2.28	-2.52	-4.43		{"name":"U.S. Average Individual Income (2018)","series":[["White",65.34],["Mixed \/ Other",7.28],["Asian",7.52],["Black",9.43]],"cast":[{"name":"White","y":85,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5,"color":"#55BF3B"},{"name":"Asian","y":5,"color":"#90ee7e"},{"name":"Black","y":5,"color":"#f45b5b"}]}
World population (2019) Percentage	14.24%	1.92%	31.25%	14.47%		{"name":"World population (2019) ","series":[{"name":"Mixed \/ Other","y":14688882870,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Latino","y":42991259469,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Indigenous","y":10971786583,"color":"#aaeeee","sliced":true,"selected":true},{"name":"White","y":108889096410,"color":"#2b908f","sliced":true,"selected":true},{"name":"Black","y":110601821551,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Asian","y":238860161621,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Arab","y":67406299429,"color":"#DF5353","sliced":true,"selected":true},{"name":"Indian","y":167470202093,"color":"#7798BF","sliced":true,"selected":true},{"name":"Jewish","y":2568698093,"color":"#ff0066","sliced":true,"selected":true}],"prefix":""}	NOTE: ZR is the first organization to ever create a global buying power divided by race. Essentially we just took data from CIA.gov FactBook, UN Population Estimates, and The World Bank's Population Estimates / Purchasing Power Parity Per Capita.
World population (2019) Representation	+70.76	+3.08	-26.25	-9.47		{"name":"World population (2019) ","series":[["White",14.24],["Mixed \/ Other",1.92],["Asian",31.25],["Black",14.47]],"cast":[{"name":"White","y":85,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5,"color":"#55BF3B"},{"name":"Asian","y":5,"color":"#90ee7e"},{"name":"Black","y":5,"color":"#f45b5b"}]}
World Buying Power Percentage	36.48%	1.81%	29.46%	6.38%		{"name":"World Buying Power","series":[{"name":"White","y":3010602822170000,"color":"#2b908f","sliced":true,"selected":true},{"name":"Latino","y":771525888400000,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Jewish","y":91700962050000,"color":"#ff0066","sliced":true,"selected":true},{"name":"Black","y":526264226360000,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indigenous","y":174285727610000,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":148984454560000,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Arab","y":526400066100000,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":2431392083750000,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Indian","y":572687873900000,"color":"#7798BF","sliced":true,"selected":true}],"prefix":"$"}	NOTE: ZR is the first organization to ever create a global buying power divided by race. Essentially we just took data from CIA.gov FactBook, UN Population Estimates, and The World Bank's Population Estimates / Purchasing Power Parity Per Capita.
World Buying Power Representation	+48.52	+3.19	-24.46	-1.38		{"name":"World Buying Power","series":[["White",36.48],["Mixed \/ Other",1.81],["Asian",29.46],["Black",6.38]],"cast":[{"name":"White","y":85,"color":"#2b908f"},{"name":"Mixed \/ Other","y":5,"color":"#55BF3B"},{"name":"Asian","y":5,"color":"#90ee7e"},{"name":"Black","y":5,"color":"#f45b5b"}]}
Notes		The "Mixed / Other" categories overlap, and the 2 or more category was not an option until the 2000 Census. So for the combined column, all data will be taken from the "Other" column except for 2000, 2010, & 2020. For those, the average between the "2 or More Races" and "Some Other Race" will be used.	The US Census considers Pakistani, Sri Lankan, Indian, and Bangladeshi as Asians. At ZR we group Pakistanis with the Arab world. And we group Sri Lankan and Bangladeshi with India because 1.) they are all genetically similar as "South Asians and 2.) there are only a handful of actors from those regions in our database. However, you are viewing the "Asian Alone" category from the US Census when comparing it with Domestic representation. Also note that the 2000 and 2010 estimates include MultiRacial Asians not just "Asian Alone" estimates, and in some categories they include Native Hawaiians as "Asian." So there is a margin of error less than 1% and some inconsistencies with the grouping.

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Parental Guide

Parental Guide: +add

This film gets a 1.45/5 family friendly score

MPAA Certification	No MPAA rating found yet. Add Family Friendly Rating?
IMDb Rating https://www.imdb.com/title/tt2103264/parentalguide last updated: 2024-10-25Update data
Commonsensemedia Rating https://www.commonsensemedia.org/movie-reviews/emperor last updated: 2024-10-25Update data
Message 3/5	A man faces a complex decision. In spite of great pressure -- and after a great deal of mental struggle -- he eventually chooses compassion over revenge. And he manages to pass this compassion on to others.
Role model 2/5	The main character shows strong empathy and tolerance toward another culture, though his own personal behavior is sometimes rude and pushy.
Violence 3/5
Sex 2/5	The main character has a romantic relationship that includes lots of kissing, but nothing more sexual than that is shown or suggested. There's a brief scene of a "wild" college dance, with students kissing in the background.
Language 3/5	Language is fairly infrequent, and only General MacArthur uses it. He says "f--king" once and uses "son of a bitch," "s--t," "balls," "hell," "piss," "damn," and "goddamn" at least once each.
Drugs 3/5	Fellers drinks beer and gets drunk in a bar and later drinks whisky and gets drunk in his office. There are no apparent after affects. He smokes cigarettes throughout (accurate for the era). Many minor characters are also seen drinking and smoking in the background.

Methodology

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Douban

rating: 6.4/10

Kinopoisk

rating: 6.4/10

OFDb

rating: 5.9/10

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Emperor

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