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Disaster Casualties Visualization Tool: Kfar Etzion Massacre: 1948

129 Dead Men and Women

The Kfar Etzion massacre was a massacre of 129 Jews by the Arab Legion on May 13, 1948, the day before the Israeli Declaration of Independence.

This was a person. He could play cricket. He always had a clean car. This was a person. She  collected figurines. This was a person. She just had the bandages removed from  plastic surgery. This was a person. She was cockeyed. She wore bow ties. This was a person. He took a lot of photos. He ate a lot of fish. This was a person. She never carried cash. This was a person. She ate a lot of hot dogs. She always wore a hat. This was a person. She loved chocolate. This was a person. He brought great food to social gatherings. He could play cricket. This was a person. He made pie. This was a person. She was a cat person. She was a vegetarian. This was a person. He was living with his sister. This was a person. He had a sexy phone voice. He couldn't stand having the air-conditioner blow on   himself . This was a person. He was thrifty. He could play trumpet. This was a person. He  was a DJ. He was afraid of the water. This was a person. He was afraid of the water. This was a person. She wanted to learn magic. This was a person. He was gluten intolerant. He looked like a cartoon. This was a person. She  was learning to speak French. She  only ever had sex with one person. This was a person. She was homophobic. This was a person. He couldn't grow a mustache. This was a person. He  scalped tickets This was a person. He was a trivia master. This was a person. He  was playing nine games of Words with Friends on  his  phone. This was a person. She was always in a hurry. She took careful notes after every meal. This was a person. She loved pot. This was a person. He always brought reusable bags into the store. This was a person. She was a dog person. She could play banjo. This was a person. She was kind of addicted to ebay. This was a person. He had a bunch of tattoos. This was a person. She wanted to learn magic. She could play cricket. This was a person. She was good at job interviews. This was a person. He  had a hangover yesterday. This was a person. He  finished reading all of the works of Homer. This was a person. He  was playing nine games of Words with Friends on  his  phone. This was a person. He was a good dancer. This was a person. He has four overdue books.  This was a person. She survived cancer. This was a person. She helped strangers. This was a person. He watched a lot of sports on TV, but never played them  himself. This was a person. She loved chocolate. She had an unfortunate nickname. This was a person. She ate a lot of fiber. This was a person. She had an awesome home theatre. This was a person. He occasionally shop lifted. He never tried gin. This was a person. She was a vegetarian. She had bonsai trees. This was a person. She had crazy hair colors. This was a person. He  was learning to speak French. This was a person. He was thrifty. This was a person. He  had a personal injury lawsuit working its way through the courts. This was a person. She ate a lot of fish. This was a person. He was lactose intolerant. This was a person. He took careful notes after every meal. This was a person. She had crazy hair colors. This was a person. He occasionally shop lifted. This was a person. He had a lot of Beatles records. This was a person. She had a gun. This was a person. He was working  his  way through all of the shows on Netflix. This was a person. He brought great food to social gatherings. This was a person. He  played soccer every weekend. This was a person. She was good at job interviews. She had long fingernails. This was a person. He excelled at woodworking. He has a music afficianado. This was a person. She  was a teacher. This was a person. He had a lot of music on vinyl. This was a person. He  collected figurines. This was a person. He  was a historian. He couldn't grow a mustache. This was a person. She  was sort of selfish in bed. She made  her  own beer and was kind of stingy with it. This was a person. She was allergic to peanuts. She loved chocolate. This was a person. He  had a personal injury lawsuit working its way through the courts. He was an awful driver. This was a person. She  volunteered at a middle school, because  she  had a crush on one of the other tutors. She  was sleeping with  her  ex. This was a person. He was kind of addicted to ebay. This was a person. She never carried cash. She had a gun. This was a person. He  was a translator. This was a person. He had a sexy phone voice. This was a person. She was afraid of the water. This was a person. She  was kind of an awesome lover. This was a person. He got out of jail two years ago and never reunited with his family. This was a person. She  was a virgin. This was a person. She had extensions. This was a person. She had a podcast. This was a person. He excelled at woodworking. This was a person. She was a glassblower. She ate a lot of raisins. This was a person. He took careful notes after every meal. He loved Elvis. This was a person. She snored. This was a person. She threw a lot of parties. This was a person. He took careful notes after every meal. This was a person. She loved chocolate. This was a person. She had crazy hair colors. This was a person. She was always in a hurry. She had a lot of Beatles records. This was a person. He had crazy hair colors. This was a person. He was rough and tumble. This was a person. He could fix anything. He made pie. This was a person. He could play cricket. He was a good dancer. This was a person. She slept around. This was a person. She taught guitar. This was a person. He was polite to salesmen. He was very good at cleaning. This was a person. She  volunteered at a middle school, because  she  had a crush on one of the other tutors. This was a person. He  could always get tickets. This was a person. He helped people. This was a person. She did not own a fridge. This was a person. She had a lot of music on vinyl. She constantly wore sunglasses. This was a person. She had a green thumb. This was a person. She was a glassblower. This was a person. He was a Mac evangelist. This was a person. He was the unofficial relationship guru among   friends. This was a person. He spends a lot of time watching tennis. This was a person. He wore earphones all the time. This was a person. She  had VD. She was afraid of heights. This was a person. She  was a drunk. This was a person. He  was a plumber. This was a person. She was a dog person. She wrote for the newspaper. This was a person. He ate a lot of fish. This was a person. He  played soccer every weekend. This was a person. She was a cheapskate. This was a person. She had a podcast. This was a person. She had a bunch of cameras. This was a person. He loved nachos. This was a person. He  loved to make out. This was a person. He was the richest of  his friends. He was lactose intolerant. This was a person. He never drank coffee. This was a person. She  was awaiting judgement for a DUI last month. This was a person. He just had  his car stereo repaired. This was a person. He survived cancer. This was a person. She wore a lot of jewelry. This was a person. She was a skilled woodcarver. This was a person. She threw a lot of parties. This was a person. He had a lot of Beatles records. He did not sleep with a pillow. This was a person. She was gluten intolerant. She was the unofficial relationship guru among   friends. This was a person. He did not own a fridge. This was a person. He was polite to telemarketers.

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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