The Banana massacre Tragedy Casualties Visualization Tool - Cockeyed.com

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Disaster Casualties Visualization Tool: The Banana massacre: 1928

100 Dead Men and Women

The Banana massacre was a massacre of striking workers for the United Fruit Company on December 6, 1928 in the town of Ciénaga, Colombia. The number of dead has not been accurately noted.

This was a person. He wore Spandex. He sang at parties.

This was a person. He took a lot of photos.

This was a person. She spends a lot of time watching tennis.

This was a person. She threw a lot of parties.

This was a person. She ate a lot of chinese food. She was very careful about conserving gasoline.

This was a person. He went to the horseraces. He had just paid a crapload of money to get teeth fixed.

This was a person. She could always get tickets.

This was a person. He had a bunch of tattoos.

This was a person. He ate a lot of chinese food.

This was a person. He was a crossword whiz.

This was a person. He was polite to salesmen.

This was a person. He was left-handed.

This was a person. He didn't get along with animals.

This was a person. He was afraid of the water.

This was a person. He was a secret Buddahist.

This was a person. He was 4 days sober. He had been having trouble tying his shoes because he pulled a muscle in his abs.

This was a person. He smoked pot at music festivals.

This was a person. He got a terrible haircut a few days ago and shaved his head to escape from it.

This was a person. He loved cigarettes. He played a lot of social card games.

This was a person. She was a secret Buddahist.

This was a person. He had an awesome home theatre.

This was a person. He watched a lot of sports on TV, but never played them himself. He constantly wore sunglasses.

This was a person. She picked up litter. She made scrapbooks.

This was a person. He grew up on a farm.

This was a person. She had a lot of Beatles records.

This was a person. He was thrifty.

This was a person. He had an awesome home theatre. He took a lot of photos.

This was a person. She dropped her work laptop last week, destroyed it and couldn't sleep for days.

This was a person. She was afraid of the water.

This was a person. She was a DJ.

This was a person. He always had a clean car.

This was a person. She ate a lot of raisins.

This was a person. He ate a lot of fish.

This was a person. He ate a lot of chinese food.

This was a person. He ate a lot of fish.

This was a person. He ate the food at convenience stores.

This was a person. She was an expert barbecuer. She fixed bikes.

This was a person. She has a suit at the cleaners. She could fix anything.

This was a person. She was always in a hurry. She loved Elvis.

This was a person. She played World of Warcraft

This was a person. He always wore a hat.

This was a person. He had an unfortunate nickname. He was cockeyed.

This was a person. She ate a lot of hot dogs.

This was a person. He wore Spandex. He wore a lot of hats.

This was a person. He played piano. He never ate breakfast.

This was a person. He was rebuilding an engine.

This was a person. He was training to run a marathon. He was a translator.

This was a person. She knew a lot of cops. She was the richest of her friends.

This was a person. He was rough and tumble.

This was a person. He was a cat person.

This was a person. He called in sick to work 9 times last month and was written up at work.

This was a person. He wore a lot of jewelry.

This was a person. She was always in a hurry.

This was a person. She could fix anything.

This was a person. She ate a lot of kale.

This was a person. She had extensions.

This was a person. He didn't get along with animals.

This was a person. She chewed gum constantly.

This was a person. She watched a lot of sports on TV, but never played them herself.

This was a person. He always bought flowers for his desk.

This was a person. She was an awful driver.

This was a person. He had an awesome home theatre.

This was a person. He taught guitar.

This was a person. He always had gum.

This was a person. He was learning to speak French.

This was a person. She had bonsai trees. She could play cricket.

This was a person. He ate a lot of fish.

This was a person. She had been having trouble tying her shoes because she pulled a muscle in her abs.

This was a person. He was sporty.

This was a person. He just had the bandages removed from plastic surgery.

This was a person. She did not own a fridge. She was a cheapskate.

This was a person. He watched a lot of sports on TV, but never played them himself.

This was a person. She was a historian.

This was a person. She collected figurines.

This was a person. She has a suit at the cleaners.

This was a person. She was sort of selfish in bed. She was a teacher.

This was a person. She tutored kids.

This was a person. She could juggle. She loved pot.

This was a person. She played a lot of social card games.

This was a person. She was playing nine games of Words with Friends on her phone. She was a crossword whiz.

This was a person. She prefered bread without crusts.

This was a person. He ate a lot of chinese food.

This was a person. She always had a clean car.

This was a person. She played chess.

This was a person. He was allergic to peanuts. He loved cigarettes.

This was a person. She was a glassblower.

This was a person. She was a historian.

This was a person. He was a crossword whiz.

This was a person. He could play cricket. He never finished the book club book.

This was a person. He was a pharmacist.

This was a person. She ate a lot of hot dogs. She was very good at cleaning.

This was a person. She was allergic to peanuts.

This was a person. She was afraid of flying. She could always get tickets.

This was a person. He was a trivia master.

This was a person. She smoked pot at music festivals.

This was a person. He spent a lot of time with old people. He couldn't stand having the air-conditioner blow on himself .

This was a person. He was a cat person.

This was a person. He excelled at woodworking.

This was a person. She wore a lot of jewelry. She played piano.

This was a person. She was living with her sister. She was learning to use CAD software.

View a different tragedy with the Disaster Visualization Tool

Jonestown | The Titanic | Kent State Shootings | My Lai | Lockerbie bombing | Kent State Shootings | Tiananmen Square Massacre | The Banana massacre | The Boyd Massacre | Mountain Meadows massacre | Kfar Etzion Massacre | Sharpeville Massacre | The Miami Showband Massacre | The Novocherkassk massacre | Tokyo Subway Sarin attack | Sinking of the Titanic | The Happy Land Fire | Brooklyn Bridge stampede | 1990 Pilgrim Stampede | Luxor hot air balloon crash |

Mouse-over body descriptions are randomly generated, intended to inject humanity into the raw number of dead. It cannot accurately represent the actual people who died in the tragedy.

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