Hollywood + data

23 January, 2012 (22:53) | data visualization | By: jerome

Ever heard of the Information is Beautiful awards? It’s visualization competitions a monthly visualization competition put together by David McCandless of Information is Beautiful fame.

Part of it are monthly competitions that run on a curated dataset. Jen Lowe and I are making a team for the current one about the movie industry and we are going to deliver a competitive entry! even our drafts are rocking! But, while we were looking for that one great idea I explored the data.

Part of the dataset is the total box office earnings of over 600 of the movies released in the US in the last 5 years. What I did is cross that list with the user-contributed plot keywords on imdb. Then, I ran a regression on that to find out how much each keyword would generate in the box office? (I only kept those keywords mentioned over 5 times, that’s just over 2500, because else the full list is  20,000+). The full list is at the end of the article.

ok the main motivation for doing this was after seeing the Tree of Life.

Yeah!

Tree of Life was a contemplative family drama, but Terrence Malick turned that into a totally awesome contemplative family drama by throwing in the mix dinosaurs and outer space scenes. I would have liked to prove that a liberal addition of dinosaurs can turn every movie into a better movie, alas, the numbers think otherwise. Movies with dinosaurs will make $500k less in the box office than movies without. For the effort, directors might just as well use dogs instead (movies tagged with “dog” make an extra $4.6m).

and one can see why.

What else can we tell from the numbers?

Believe it or not, nudity will not generate extra profit – movies tagged with nudity will make $2.9m less. Full frontal nudity makes a movie lose even more money. “Partial nudity” or “implied nudity” is ok, though. Now sex is another story. Sex will make a movie get another $6.7m (actors should just keep their clothes on).

Violence is always a hit, too! Explosions generate $6.6m profit, murder is a classic, too – +$2.7m. And “nude woman murdered” is +$1.2m, so if you really need nudity in a movie… Then, you have to choose your weapons – pistol, rifle and rocket launcher make $5.6m, $5.5m and $5.4m respectively. Axes and knives work, too (+$1.4m and +$2.0m) but “knife throwing” or “threatened with a knife” is a no-no (-$2.8m and -$3.5m).

Success in Hollywood starts with a title. Ideally, it should have 2 words, include the name of a character and a place name and punctuation. Then, one character should say the name during the movie. If you pull this out, your movie will make almost $40m extra.

Other very lucrative elements include: a hotel, a gas station, trains, buses, male-female and mother-son relationships, love triangle, and the aforementioned sex and explosions. Also, if you get a character spit on another in the face, that’s an extra $7m.

Caveats:

this is user contributed data so it is quite messy. Some of the keywords are very similar and just because a movie is tagged with one doesn’t mean it’s tagged with the other – like “jew” and “jewish” for instance, “samurai sword” and “katana sword” or many such pairs. And just because a movie is not tagged with a specific keyword doesn’t mean it shouldn’t. Out of the set, there are “only” 135 movies with male-female relationship, compared with 186 tagged with “husband wife relationship”… and regardless, there are too few samples to be really accurate. And now, on with the data!

How to read this: Movies revenues start from a base value, a bit over $43m, and then for each keyword they are tagged with, they can be expected to generate the value in the leftmost column in additional revenue (or lose that much money if that’s a negative value).
Let’s suppose I have a script idea with an alien invasion, giant robots, laser guns, an action heroine and, of course, explosions. Well, I can expect it to make circa $55m.

43.38558
11.01647 Based On Novel 108
10.9297 Title Spoken By Character 205
9.978092 Voice Over Narration 98
9.225159 Male Female Relationship 135
8.29086 Character Name In Title 142
8.2029 Mother Son Relationship 158
7.566741 Train 66
7.469721 Bus 48
7.429563 Punctuation In Title 50
7.031444 Spit In The Face 19
6.704495 Sex 74
6.603162 Explosion 150
6.580685 Love Triangle 37
6.400931 Character Says I Love You 44
6.203932 Place Name In Title 25
6.152445 Hotel 64
6.093435 Two Word Title 49
6.048043 Beautiful Woman 91
6.046778 Gas Station 25
6.02446 Piano 32
5.947599 Boyfriend Girlfriend Relationship 115
5.889154 Bicycle 33
5.879267 Kiss 125
5.850736 Flashback 215
5.787691 Railway Station 14
5.749066 Singing In A Car 40
5.737487 Father Son Relationship 191
5.699003 Prostitute 35
5.67702 Cell Phone 148
5.64624 Pistol 178
5.629091 Premarital Sex 49
5.547501 Shot In The Leg 67
5.538875 Looking At Self In Mirror 40
5.514411 Rifle 61
5.485783 Nonlinear Timeline 39
5.473053 Computer 50
5.436822 Vomit 94
5.436589 Three Word Title 43
5.405976 Rocket Launcher 30
5.383704 Head Bashed In 7
5.382445 Woman Smoker 7
5.354009 Stabbed In The Stomach 20
5.280325 Texas 13
5.228234 Aerial Shot 20
5.183339 Shot In The Back 103
5.140946 Summer 9
5.125163 Faked Death 16
5.112674 Piano Playing 11
5.090634 1950s 14
5.077975 Marriage 70
4.987133 Los Angeles California 73
4.96386 Blood 207
4.916601 Shot Multiple Times 12
4.822637 Robbery 47
4.804778 Scene During End Credits 84
4.792221 Death Of Protagonist 20
4.77868 3 Dimensional 36
4.710419 Small Town 41
4.667171 Neck Brace 7
4.661585 Drunkenness 102
4.614724 Shot In The Chest 162
4.58988 Dog 125
4.570129 Remake 50
4.559715 Person On Fire 63
4.540027 Burning Building 7
4.520416 Face Slap 80
4.516572 Shot In The Face 41
4.516426 Violence 154
4.509856 Alarm Clock 11
4.507561 Shot In The Head 122
4.503419 District Attorney 10
4.43994 Wedding 60
4.385918 Oral Sex 12
4.384226 Character Repeating Someone Else's Dialogue 66
4.341869 Phonograph 10
4.290248 Psychopath 32
4.23124 No Opening Credits 143
4.227286 Playing Piano 7
4.214099 Young Version Of Character 28
4.206819 Police Officer Killed 70
4.198599 Based On Book 27
4.161716 Best Friend 44
4.134605 Prayer 43
4.127119 Digit In Title 44
4.125824 Rear Entry Sex 12
4.07263 Female Protagonist 46
4.037197 Woman Slaps A Man 6
4.018396 One Word Title 107
3.954351 Shot To Death 140
3.869408 Number In Title 68
3.866646 Southern Accent 15
3.861538 Beaten To Death 26
3.8323 Revenge 105
3.828182 M 16 9
3.807658 Dance 39
3.782046 Woman In Bra And Panties 16
3.781513 Flat Tire 6
3.775069 Kitchen 50
3.759801 Sadism 15
3.716672 Fighter Jet 12
3.702997 Letter 44
3.683648 Cruelty 11
3.67165 Friendship 160
3.620449 Blood On Camera Lens 19
3.599451 One Day 14
3.573374 Coma 11
3.553269 Liar 32
3.550136 Narrated By Character 16
3.542962 Rain 94
3.52033 Studio Logo Segues Into Film 19
3.52031 Race Against Time 33
3.513768 Infidelity 55
3.50176 Bludgeoning 6
3.435638 Urination 64
3.433887 Spanking 10
3.429957 Affair 16
3.42752 Cowboy Hat 16
3.416226 Alien Invasion 14
3.409104 Security Guard 33
3.408259 Murder Investigation 10
3.403385 Helicopter 96
3.398969 Break Up 22
3.397207 Third Part 19
3.379592 Camera Focus On Female Butt 9
3.360536 Surprise Ending 143
3.351977 Birth 13
3.349504 Department Store 7
3.335839 Military Base 6
3.334879 Destruction 10
3.314636 Controversy 12
3.307408 Sociopath 14
3.260985 Supernatural 12
3.260223 Ambiguous Ending 15
3.250392 School 46
3.244681 Burned Alive 44
3.233657 Deputy 8
3.232169 Crushed By A Car 17
3.229493 Cult Favorite 74
3.223396 Black Bra And Panties 6
3.222142 Pregnancy Test 10
3.213285 Train Ride 7
3.203048 House On Fire 11
3.201547 Doggystyle Sex 7
3.192427 Scissors 12
3.180222 Destroyed City 6
3.17603 Map 39
3.174533 Love 107
3.164935 Depression 19
3.164348 Gore 64
3.152872 Bartender 20
3.151337 Pregnancy 70
3.131467 City Name In Title 11
3.104769 Machine Gun 113
3.104581 Gunfight 44
3.084597 Diner 41
3.080635 Ghost 21
3.074354 Undressing 33
3.056532 Crushed To Death 49
3.034691 Cleavage 23
3.01604 Prisoner 27
3.012131 News Report 43
3.00241 Office 15
2.99479 Shot In The Arm 37
2.992653 Cigar Smoking 27
2.991858 Boy 58
2.983369 Lawyer 56
2.976002 Friendship Between Women 6
2.971588 Blackmail 20
2.96858 Army 37
2.952323 Rat 26
2.932456 Stabbed In The Chest 93
2.915709 Marijuana 36
2.908199 Toilet 29
2.891019 Attorney 14
2.889739 Man Punching A Woman 15
2.889545 Title Appears In Writing 41
2.867293 Death Of Friend 66
2.856384 Whistling 9
2.848002 Rooftop 63
2.844533 Spaceship 22
2.844413 Sequel 79
2.830977 New York City 109
2.829935 U.S. Air Force 10
2.81014 Child In Peril 86
2.797008 Apology 26
2.794885 Autopsy 8
2.766401 Water 22
2.76586 Rampage 6
2.76511 Loss Of Virginity 10
2.763551 African American 46
2.755285 Airplane 77
2.748839 Food 51
2.739722 Humvee 7
2.732625 Golf Club 7
2.731552 Axe 43
2.727385 Teen 25
2.721565 Hospital 110
2.701111 Bare Chested Male 174
2.700862 Hallucination 40
2.700319 Tent 29
2.698122 Murder 216
2.697655 Brutality 18
2.694648 Shopping Mall 7
2.689665 Sailing Ship 7
2.688108 Evacuation 17
2.685551 Employer Employee Relationship 19
2.680226 Missile 25
2.675465 U.S. Army 26
2.662061 Pianist 17
2.657389 Drawing 26
2.655393 Karaoke 10
2.653747 Tank 25
2.637778 Police Officer Shot 17
2.630431 Teenage Boy 49
2.624766 Prologue 65
2.617668 Fear 52
2.60366 Fire 100
2.603136 Alien 36
2.599799 Cityscape 8
2.597033 Independent Film 10
2.592572 Female Rear Nudity 38
2.587849 Double Barreled Shotgun 13
2.582282 Air Strike 6
2.581882 Slow Motion Scene 70
2.581119 Reflection 7
2.579659 Insect 10
2.578415 E Mail 17
2.577775 Sniper 45
2.571637 Panties 48
2.566943 Parachute 23
2.559685 Convenience Store 12
2.557557 Facial Scar 8
2.552169 Friend 85
2.549232 Wilhelm Scream 34
2.537737 Graveyard 18
2.537527 Jealousy 46
2.537257 Husband Wife Relationship 186
2.532388 Body Torn Apart 8
2.516066 Bruise 11
2.50799 Character's Point Of View Camera Shot 35
2.507902 Lesbian 19
2.507798 Sadist 6
2.502953 Childbirth 17
2.502167 Book 51
2.499631 Corpse 133
2.49426 Chick Flick 22
2.488826 Shootout 118
2.487724 Condom 14
2.484781 Teenage Girl 51
2.484076 Hanged Man 17
2.481457 Job Interview 12
2.476003 Single Mother 35
2.474626 Swimming Pool 62
2.472312 Prom 7
2.4669 Torso Cut In Half 23
2.436416 Courtroom 20
2.42972 Starts With Narration 13
2.417421 Hit With A Shovel 9
2.416896 Casino 23
2.406878 Shot In The Forehead 62
2.384468 Escape 84
2.38222 Product Placement 54
2.381239 Exploding Ship 11
2.372949 Police Car 38
2.359501 Artist 18
2.356472 Restaurant 86
2.353561 Circular Staircase 6
2.353458 Writer 30
2.342151 Robot 33
2.315538 Pizza 13
2.315204 Unwed Pregnancy 7
2.312343 Neo Noir 18
2.312169 Cemetery 53
2.308813 Topless Female Nudity 68
2.306563 Winter 8
2.304189 Game Playing 8
2.303714 Gay Slur 27
2.302093 Super Strength 18
2.293502 Truth 6
2.292263 Gasoline 14
2.291891 Gurney 7
2.289659 Money Falling Through The Air 11
2.279531 Pajamas 8
2.27428 Divorce 37
2.274121 Stabbed To Death 55
2.260093 Death 199
2.254603 Giant Robot 9
2.243596 Blood Spatter 127
2.24063 Police Chase 24
2.239712 Trust 20
2.236241 Stabbed In The Heart 6
2.231905 Double Decker Bus 9
2.229004 Suburb 13
2.224421 High Tech 7
2.222413 Cocaine 24
2.217331 Partial Female Nudity 6
2.213752 Talking Animal 23
2.211055 Mental Hospital 7
2.21064 Time Travel 11
2.20539 Title Directed By Female 28
2.197722 Police Officer 34
2.196538 Fictional War 33
2.194686 Planet 17
2.193423 Veterinarian 7
2.188918 Death Of Son 17
2.188624 Media Coverage 9
2.188139 Illegitimate Child 6
2.18239 Severed Arm 40
2.176112 Singing 84
2.166325 Thong 16
2.157461 Spacecraft 13
2.157368 Electrocution 41
2.148292 UFO 9
2.137909 Decapitation 48
2.137845 Scene After End Credits 26
2.134213 Sledgehammer 7
2.133101 Theatre Audience 12
2.131795 Flashlight 60
2.130494 Old Flame 9
2.122467 Exploding Bus 7
2.111516 Foot Chase 74
2.108804 Mine 8
2.105497 Slow Motion 54
2.092328 London England 38
2.082263 Musician 23
2.081966 Chandelier 17
2.080916 True Love 13
2.078839 Sex Scene 54
2.075914 Physician 9
2.070329 Hollywood California 9
2.069371 Cnn Reporter 7
2.045122 Babysitter 10
2.041997 Alternate Reality 9
2.039635 Newspaper 40
2.037686 Framed For Murder 12
2.036944 Apostrophe In Title 20
2.035902 Alcohol 18
2.032397 Exploding Body 64
2.030869 Accidental Killing 8
2.025309 Near Death Experience 12
2.020871 Talking To The Camera 12
2.008779 Knife 104
2.008422 Sister Sister Relationship 46
2.003921 Waitress 31
2.002322 Gun 73
1.999843 Showdown 50
1.990494 Secret Passage 6
1.99015 Grief 15
1.984949 Vandalism 9
1.982138 Fantasy Sequence 27
1.975828 Demon 21
1.973049 C4 Explosives 8
1.97066 Dynamite 13
1.966198 Kicked In The Stomach 38
1.951852 Surrealism 39
1.945289 Dinner 23
1.94177 Anger 26
1.930417 Warrior 54
1.928132 Time 6
1.92141 Bed 17
1.919331 Architect 8
1.91824 Little Girl 17
1.916919 Gas Mask 19
1.914259 Coffin 27
1.907891 Car Accident 91
1.90281 Wheelchair 36
1.897532 Menstruation 6
1.897394 Survival 33
1.892948 Camel Toe 6
1.892829 Escalator 9
1.889513 Video Store 7
1.878208 Pancake 6
1.862681 Deceit 12
1.859214 Philadelphia Pennsylvania 7
1.850481 Psychiatrist 15
1.847398 Statue 23
1.840783 Siren 11
1.838405 Coincidence 8
1.832663 Elevator 71
1.828607 Father Daughter Relationship 145
1.82717 Mother Daughter Relationship 112
1.823635 Infant 8
1.81726 Amusement Park 6
1.808548 Evil Man 33
1.801437 Actress 13
1.796545 Snowing 14
1.795661 Neighbor 25
1.793233 FBI 27
1.791299 Sheriff 33
1.777066 Bank Robbery 14
1.77701 Uh 1 Huey Helicopter 8
1.769411 Back From The Dead 29
1.764009 Magic 23
1.759536 Drone 8
1.759119 Reference To William Shakespeare 7
1.754258 Grandmother Grandson Relationship 14
1.746794 Punched In The Face 148
1.746557 Survival Horror 16
1.744166 Tragic Event 11
1.74258 Rescue Mission 7
1.734431 Bazooka 8
1.731729 Terrorist 26
1.730159 Cat And Mouse 6
1.729232 Bench 9
1.728905 Meteor 7
1.724943 Banana 6
1.718215 Bomb 60
1.709952 Animal In Title 29
1.701139 Implied Nudity 12
1.700967 Abortion 7
1.700178 Orphan 33
1.69898 Graffiti 11
1.695889 Sacrifice 18
1.694772 Whiskey 10
1.690871 Party 85
1.690685 Dancing 110
1.68562 Thrown Through A Wall 14
1.681228 Rape 24
1.680435 Talking To Self In Mirror 6
1.678013 Poster 8
1.675478 Running Away 6
1.671244 Blue Panties 7
1.659671 Sailboat 14
1.646346 Fireball 15
1.641142 Brawl 72
1.637756 Alternate World 6
1.631237 Horse And Carriage 7
1.627765 Immortality 16
1.625339 Footprint 7
1.624377 Travel 17
1.616072 Buried Alive 7
1.610091 High School 51
1.610043 Baby 32
1.600479 Night Vision 10
1.592658 Key 16
1.591923 Death Of Sister 10
1.578428 Newscast 17
1.577475 Retirement 10
1.573182 Criminal 15
1.567005 Superhuman Strength 6
1.555611 Leg Injury 8
1.553289 Attraction 7
1.55302 Zoo 10
1.549528 Disaster 8
1.549209 Sadness 12
1.54849 Bar 113
1.548273 IMAX Version 8
1.547101 Man Wearing A Wig 7
1.541334 Scientist 47
1.539754 Zombie 9
1.539686 Bedroom 15
1.537147 Vodka 8
1.537032 Giant 14
1.535406 Love At First Sight 10
1.53301 Walkie Talkie 29
1.53048 Hiding In A Closet 17
1.530076 Period In Title 8
1.528577 Laundromat 7
1.527948 Computer Animation 26
1.525873 Electric Shock 7
1.52578 Theft 29
1.524732 Grave 15
1.52005 Chicago Illinois 20
1.517736 Adoption 21
1.516048 Police Station 40
1.512441 Gatling Gun 24
1.509041 Stuffed Animal Toy 6
1.5043 Crowbar 6
1.503577 Guitar 30
1.502802 Vault 9
1.499879 Miscarriage 7
1.498675 Grenade Launcher 15
1.494071 Mansion 29
1.493068 Lie 45
1.492603 Old Dark House 8
1.487566 Filmed Killing 14
1.485836 Bride 8
1.485596 Snow 68
1.481724 Butt Slap 17
1.481413 Found Footage 6
1.478572 Human Sacrifice 10
1.478294 Covert Operation 9
1.478009 Rope 17
1.474201 Mental Institution 9
1.471173 Nightclub 42
1.470549 Watching A Movie 14
1.469098 Locker Room 18
1.465314 Hit By Car 54
1.463814 Shot In The Eye 15
1.459632 Elephant 14
1.457958 Thunderstorm 9
1.451709 Tea 8
1.448676 Train Explosion 8
1.440871 Secretary 17
1.437521 Wealth 16
1.436435 Thrown Off A Balcony 6
1.434914 Gps 7
1.431374 Button 6
1.429193 Upskirt 12
1.423783 Inventor 10
1.420316 Dreadlocks 10
1.419305 Desert 65
1.407842 Nude Woman Murdered 12
1.400761 Survivor 10
1.397725 Plan 6
1.39766 Giving Birth 8
1.390163 Broken Engagement 6
1.38858 Baseball 12
1.387794 Business 8
1.384034 Supermarket 17
1.383142 Opening Action Scene 16
1.379973 Ice Cream 12
1.37935 Lightning 29
1.37663 Mouse 13
1.375497 Sushi 7
1.373068 Hand Grenade 13
1.371566 Invasion 8
1.371058 Basement 19
1.370636 Video Surveillance 22
1.367507 Axe Murder 10
1.364543 Tunnel 32
1.362012 Lieutenant 13
1.35778 Handcuffs 43
1.356642 Co Worker 14
1.35364 Fake Documentary 6
1.350663 Engagement 10
1.350558 Based On True Story 25
1.347575 Top Secret 11
1.344954 Female Soldier 10
1.343242 Chauffeur 7
1.340733 Hit By Train 10
1.33944 Bodyguard 19
1.338122 Needle 8
1.335817 Interracial Friendship 30
1.3356 Horse Riding 23
1.327619 Gunshot Wound 9
1.325403 Outer Space 15
1.31987 2010s 10
1.317259 Park 24
1.315694 Drowning 27
1.314067 American Flag 62
1.309458 Promotion 6
1.309277 Dismemberment 21
1.308815 Bong 17
1.308401 Girl In Bra And Panties 11
1.301211 Evil 8
1.300488 Muslim 10
1.296121 Outlaw 7
1.295144 Song 50
1.285917 Possession 8
1.284819 Thief 32
1.283818 Balloon 8
1.283535 Punishment 6
1.281962 Breaking The Fourth Wall 16
1.280966 Vampire 14
1.280569 SWAT Team 35
1.279779 Mailbox 11
1.277369 Startled 8
1.275473 Surprise Party 6
1.271444 Michigan 6
1.269634 Mask 34
1.265607 Blockbuster 55
1.264849 Dark Fantasy 7
1.26476 Art 6
1.259493 Based On Play 7
1.258136 Spiral Staircase 12
1.252713 Hot Tub 9
1.251316 Africa 7
1.250472 Quitting A Job 20
1.249799 Adultery 37
1.247514 Quarantine 7
1.240211 Jumping From A Car 7
1.239045 Candle 39
1.238428 Ménage À Trois 6
1.23805 Mockumentary 10
1.238 Park Bench 6
1.233304 Religion 31
1.231725 Rivalry 24
1.231009 Watching TV 72
1.230254 Interracial Romance 19
1.228438 Flying 23
1.227164 Screaming 14
1.227077 Demonic Possession 11
1.22435 Falling From Height 161
1.223904 Child Abuse 19
1.221272 Library 24
1.220379 Wine 31
1.220093 Hot Dog 10
1.216586 Trailer Home 9
1.213694 Subway Station 14
1.213245 Running For Your Life 6
1.212773 Villain 18
1.212657 Drugs 36
1.206907 Home Movie 12
1.206062 Overweight 6
1.202198 Rocket 17
1.200741 Loss Of Mother 21
1.200105 Soccer 10
1.197022 Loss Of Brother 13
1.196533 Fantasy World 6
1.194403 Atlanta Georgia 6
1.191169 Therapist 11
1.186703 General 28
1.186356 Slow Motion Action Scene 7
1.180546 Birthday Party 34
1.178828 Chainsaw 11
1.17875 Millionaire 8
1.174277 Grand Piano 8
1.17206 Epilogue 12
1.166439 Fake Id 7
1.160244 Marital Problem 19
1.159678 White House 11
1.157819 Shadow 12
1.156614 Battlefield 13
1.155917 Rescue 96
1.155461 Gambling 16
1.155252 Golden Gate Bridge 8
1.155054 Morgue 7
1.151445 Extraterrestrial 7
1.150858 Little Boy 18
1.150814 Moon 15
1.149725 Underage Drinking 16
1.145932 Voyeurism 8
1.13986 Redemption 28
1.138072 Doll 14
1.136496 Classroom 32
1.135507 Prejudice 13
1.135024 Shopping 7
1.132642 Deformity 9
1.132472 Suspense 30
1.130144 Assistant 9
1.130113 Bathtub 47
1.127329 Wedding Ring 16
1.125958 Flight 7
1.120938 Alcoholism 7
1.118163 Fish 19
1.116545 Pregnant Woman's Water Breaks 6
1.110514 Fraternity 7
1.109784 Loss Of Father 23
1.109073 Grocery Store 15
1.105321 Movie Theatre 7
1.103842 Secret Door 6
1.103079 Beauty Salon 7
1.103006 X Ray 7
1.101792 Expectant Mother 7
1.099328 Dark Comedy 8
1.099161 Murderer 10
1.098915 Battle Tank 8
1.097652 Power Outage 14
1.096317 Mercilessness 6
1.092785 Cousin Cousin Relationship 13
1.092683 Broken Mirror 15
1.09241 Engagement Ring 21
1.09199 Woman With Glasses 16
1.091778 Spanish 7
1.091602 Frozen Body 6
1.090693 Golf 12
1.089725 Las Vegas Nevada 21
1.089639 Remake Of Asian Film 6
1.089037 Brooklyn New York City 15
1.086887 Doorman 8
1.086858 Poverty 11
1.084267 Selfishness 11
1.076972 Accident 8
1.071272 Glock 8
1.07123 Stuffed Animal 8
1.062135 Eye Patch 18
1.06087 Arizona 7
1.055525 Film Within A Film 20
1.054043 News Reporter 14
1.05184 Tough Cop 6
1.05107 Cut Hand 13
1.044541 Roommate 22
1.044187 Farce 11
1.041367 Severed Hand 26
1.03975 First Kiss 14
1.038898 Astronaut 6
1.03592 Semiautomatic Pistol 21
1.034217 Gossip 6
1.030442 Falling In Love 17
1.030315 Volcano 11
1.028876 Dreamworks Animated Film 10
1.028583 Camera Shot Of Feet 10
1.026177 Absent Father 11
1.025554 Military 42
1.024676 Circus 6
1.018747 Man With No Name 10
1.018677 Eurocopter As350 Squirrel 6
1.018626 Exploding Building 41
1.018266 Debt 9
1.013833 Philosophy 10
1.012275 Computer Hacker 9
1.011971 Explosive 19
1.010816 Mistaken Identity 14
1.005429 Kicked In The Crotch 27
1.002514 Shot In The Stomach 26
1.001875 Crime Boss 14
1.001587 Coach 12
1.001297 Alien Contact 7
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-0.9896 Police Detective 29
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-0.99751 Hammock 6
-0.9985 Kicked In The Face 64
-0.99897 Aunt Nephew Relationship 7
-1.00023 Sequel To Cult Favorite 6
-1.00944 Blow Job 9
-1.01024 Injection 31
-1.01314 Fame 7
-1.01518 Note 12
-1.01931 Senator 14
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-1.02889 Divorcee 6
-1.02961 Amnesia 9
-1.0297 Secret Agent 30
-1.03226 Home Invasion 30
-1.03615 Lifting Person In Air 18
-1.03655 Gas Grenade 9
-1.03771 Based On Graphic Novel 11
-1.03876 Duct Tape 11
-1.04186 Impersonating A Police Officer 18
-1.04317 Confession 29
-1.04331 Uzi 21
-1.04505 Mexican 7
-1.04551 Soul 7
-1.04767 DC Comics 6
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-1.05776 Lake 24
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-1.0669 Man With Glasses 36
-1.06876 Class 20
-1.0714 Fist Fight 58
-1.07504 Prince 14
-1.07865 Band 30
-1.08041 Car Crash 97
-1.08404 Vacuum Cleaner 6
-1.08899 Gymnasium 8
-1.0909 Farmer 9
-1.09637 Stabbed In The Leg 35
-1.09695 Shot In The Neck 18
-1.09743 Heroin 10
-1.09789 Hanging Upside Down 19
-1.09855 Exploitation 10
-1.09875 Epic 17
-1.10307 Cut Arm 11
-1.10631 Origin Of Hero 12
-1.10848 Closeted Homosexual 11
-1.10998 Hippie 10
-1.11073 Weightlifting 9
-1.11145 Killed By A Propeller 6
-1.11389 Body In A Trunk 14
-1.11501 Bikini 20
-1.12094 Samurai Sword 6
-1.12515 Businessman 18
-1.12634 Card Game 8
-1.12648 Intercom 7
-1.12922 Male Camaraderie 6
-1.13223 Talking To Self 6
-1.13286 Flask 8
-1.13317 Whipping 13
-1.13421 Surveillance Footage 10
-1.13503 Split Screen 25
-1.13558 Pirate 10
-1.14557 Telephone 13
-1.14596 Ohio 7
-1.15989 Vigilantism 8
-1.165 Undercover Agent 11
-1.16893 Hand Through Chest 9
-1.16957 Priest 34
-1.1702 Cover Up 29
-1.17253 Female Frontal Nudity 29
-1.18466 Arms Dealer 11
-1.18564 Surgery 16
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-1.19063 Dead Mother 11
-1.19139 Uniform 9
-1.19806 Drinking 64
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-1.19888 Punched In The Chest 10
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-1.20323 Red Dress 14
-1.20789 Mirror 51
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-1.21581 Sunglasses 33
-1.21683 Open Ended 13
-1.21797 Dragging A Body 8
-1.22371 Reverse Footage 8
-1.22628 Italian American 7
-1.23113 Telekinesis 7
-1.23469 Storytelling 22
-1.23601 Obsession 16
-1.23657 Teleportation 21
-1.23808 Attack 10
-1.24483 Men's Bathroom 8
-1.24877 Burning Money 9
-1.25113 Speedboat 8
-1.25119 Blood On Shirt 30
-1.25133 Unfaithfulness 23
-1.25371 Taser 18
-1.2541 Female Warrior 15
-1.25678 Club 11
-1.25771 Marvel Comics 11
-1.26207 Rogue Agent 8
-1.26467 Police Raid 10
-1.26842 River 24
-1.27021 Older Man Younger Woman Relationship 15
-1.27523 Tuxedo 15
-1.28756 Male Rear Nudity 56
-1.28973 Gay Kiss 17
-1.29136 Archery 9
-1.29469 Genocide 10
-1.29699 Pregnant Woman Murdered 8
-1.2981 Jungle 22
-1.29954 Hit With A Chair 8
-1.30013 Barbecue 13
-1.30955 Telescope 16
-1.30998 Dystopia 8
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-1.31937 Impalement 68
-1.32113 Torch 24
-1.32198 Car Chase 69
-1.33219 Cafe 40
-1.33466 Shot In The Side 13
-1.34634 Celebration 8
-1.35205 Flare Gun 6
-1.35368 Flare 17
-1.35777 Head Butt 40
-1.35809 Homosexual 20
-1.37435 Jumping Off A Roof 6
-1.38771 Submarine 6
-1.39141 Handgun 23
-1.39866 1970s 20
-1.403 Death Of Wife 29
-1.40495 Junkie 12
-1.4176 Exploding Motorcycle 8
-1.4229 Fellatio 13
-1.43199 Brushing Teeth 12
-1.4354 Farm 16
-1.43853 Stealing A Car 15
-1.44758 Catholic 16
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-1.45271 Bare Breasts 65
-1.45416 No Panties 14
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-1.52054 Tough Guy 49
-1.5531 Waterfall 27
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-1.59798 Seaplane 7
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-1.62245 Drug Lord 10
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-1.69703 Heavy Rain 18
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-1.70044 Knife In The Chest 7
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-1.70632 Memory 36
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-1.73964 Times Square Manhattan New York City 11
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-1.79237 Disfigurement 21
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-1.86896 Anti Villain 9
-1.87577 Female Spy 11
-1.89728 Cyberpunk 9
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-1.9194 Stabbed In The Hand 15
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-1.94547 Silencer 34
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-1.96861 Paranoia 36
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-2.15393 Mountain 29
-2.16895 Kicking In A Door 16
-2.17237 Telephone Call 88
-2.2038 Shooting 36
-2.20742 Taxi Driver 21
-2.21739 Dark Hero 12
-2.22025 CIA Agent 15
-2.22943 Subtitled Scene 57
-2.25632 Stabbed In The Shoulder 14
-2.25828 Shotgun 86
-2.26639 Ship 26
-2.29836 Sniper Rifle 29
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-2.38421 Taxi 65
-2.3964 Security Camera 26
-2.4341 Nosebleed 24
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-2.49153 Brother Sister Relationship 88
-2.52327 Boat 46
-2.52418 CIA 19
-2.54529 Spear 24
-2.60501 Assassination Attempt 22
-2.62668 Scar 38
-2.62916 Parking Garage 28
-2.65404 Nurse 31
-2.72454 Tattoo 72
-2.73384 Double Cross 31
-2.81547 Knife Throwing 19
-2.83913 Corrupt Cop 22
-2.86158 Bare Butt 34
-2.8769 Nudity 60
-2.87872 Interrogation 48
-2.88684 Hostage 65
-3.09138 Policeman 46
-3.5041 Photograph 115
-3.516 Threatened With Knife 40
-3.64042 Motorcycle 68
-3.74255 On The Run 30
-5.32777 Betrayal 92

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Comments

Comment from David mcCandless
Time January 24, 2012 at 5:18 pm

Brilliant Jerome!

Comment from jerome
Time January 25, 2012 at 1:15 am

thanks! & thanks for the dataset. It’s been inspirational!

Comment from jerome
Time January 25, 2012 at 1:15 am

thanks! & thanks for the dataset. It’s been inspirational!

Comment from Ben Ash
Time January 25, 2012 at 3:00 pm

-3.64042 Motorcycle
-3.74255 On The Run
-5.32777 Betrayal

You can see why Ghost Rider tanked :o )

Comment from Fusselwurm
Time January 25, 2012 at 6:11 pm

@Ben Ash: No. It’s the other way round. Because Ghost Rider tanked, the plot elements “Motorcycle”, “On the Run”, “Betrayal” get a neg price tag.

Comment from jerome
Time January 25, 2012 at 6:27 pm

then there is the Nicolas Cage factor, too… I’m preparing the same with actors.

Pingback from Hollywood budgets – extended deadline | Innovar.org
Time January 25, 2012 at 7:52 pm

[...] Jermone Cukier‘s explorations of the dollar value of individual features of a plot. He cross-referenced keywords [...]

Comment from Jouss
Time January 25, 2012 at 10:04 pm

Great job !!!!!!!

If you want to add the “third dimension” to your data you could also include the year of the film… it is likely that the tags will have different values through time…

Comment from Rick
Time January 25, 2012 at 11:27 pm

I’m interested to know how you dealt with the problem of multicollinearity in your dataset, obviously words related to genres are going to have strong relationships!

http://en.wikipedia.org/wiki/Multicollinearity

Multicollinearity would prevent the individual coefficients from being meaningful.

Comment from jerome
Time January 26, 2012 at 1:45 am

easy answer – nothing. this is merely a hack, a textbook linear regression on a dataset as it is which is full of bias. so there’s no dimensionality reduction or no attempt to manually fix some variables… but mostly the problem is that there are too few samples. If that was done after the release of jurassic park 4, suddenly dinosaurs would look much more profitable :)

Pingback from Expodomain.com » Hollywood budgets – extended deadline
Time January 26, 2012 at 11:18 am

[...] Jermone Cukier‘s explorations of the dollar value of individual features of a plot. He cross-referenced keywords [...]

Comment from Jim V
Time January 27, 2012 at 4:31 pm

Very interesting stuff. I’m excited to see what you guys come up with for the challenge. I have my own submission, but it sounds like its going to get blown out of the water by more creative entries.

Would also be interested in finding out a bit more of the process behind how you and Jen designed and split up the implementation. And how long the total project took.

Good luck!

Comment from jerome
Time January 27, 2012 at 4:56 pm

thanks for your good wishes!
what we have done has nothing to do with this (except: explosions). Doing something with keywords was my original idea, but Jen came up with something better and so we move in that direction.
Good luck to you too!

Comment from mike
Time January 28, 2012 at 8:20 am

one question: i look at the IMDB keyword search page, but i can’t figure out how you were able to query it based on keyword count, or movie titles in order to join it back to the original dataset. did you write some sort of scraper for their website?

Comment from jerome
Time January 28, 2012 at 11:16 am

The tricky part was to obtain the imdb ID for each movie. Then yes the corresponding web pages (list of all keywords for each movie) were scraped.

Pingback from Episode 23: Statistics
Time February 10, 2012 at 1:51 am

[...] Jerome Cukier >> Hollywood + Data [...]

Comment from Matthew
Time February 21, 2012 at 3:37 pm

This is a neat idea, but you’re estimating an awful lot of parameters with your regression here, which is a dangerous thing to do unless you’re careful to avoid over-fitting. Which of these effects are statistically significant and how do we know we’re not just looking at noise for the parameter estimates for a lot of these keywords? Maybe worth doing some feature selection here, or at least giving p-values or confidence intervals…

Comment from jerome
Time March 9, 2012 at 3:43 pm

oh yes. I gave many caveats emptors in the post. The main problem is that keywords are not universally attributed. Also, more popular movies tend to be better described (ie with more keywords) so that the value of each keyword is artifically high. Also, as you point out, the ratio of parameters / observation is ridiculously high so overfitting is a certainty (even if the regression is regularized).
however I think that it’s possible to get some meaningful results by watching whether a few features are present in a large number of movies.

Pingback from Hollywood budgets – extended deadline | One Step To Information
Time June 22, 2012 at 5:18 pm

[...] Jermone Cukier‘s explorations of the dollar value of individual features of a plot. He cross-referenced [...]

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