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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. She had an awesome home theatre. This was a person. He  had a hangover yesterday. He  was sleeping with  his  ex. This was a person. He smoked pot at music festivals. He rode motorcycles. This was a person. She wore a lot of jewelry. She played piano. This was a person. She was a scout leader.  This was a person. He chewed gum constantly. This was a person. She  could always get tickets. This was a person. She could fall asleep anywhere. This was a person. She led the choir. This was a person. She was the unofficial relationship guru among   friends. This was a person. He  was learning to speak French. This was a person. He wore Spandex. This was a person. She  was afraid of flying. This was a person. She prefered bread without crusts. This was a person. She constantly wore sunglasses. This was a person. She  had VD. This was a person. She had a lot of music on vinyl. This was a person. She ate a lot of hot dogs. She was a hoarder. This was a person. She was a scout leader.  This was a person. She got out of jail two years ago and never reunited with her family. She  was sort of selfish in bed. This was a person. He ate a lot of fish. This was a person. He sang at parties. He led the choir. This was a person. He  had been having trouble tying  his shoes because  he  pulled a muscle in his abs. This was a person. She spent a lot of time with old people. This was a person. She  was a tailor. This was a person. He was kind of addicted to ebay. This was a person. He made scrapbooks. This was a person. He picked up litter.  This was a person. She never finished the book club book. She overtipped. This was a person. She grew up on a farm.  She played a lot of social card games.  This was a person. She has two living parents. This was a person. She  had a hangover yesterday. This was a person. He has a suit at the cleaners. This was a person. She plays fantasy football. She smoked pot at music festivals. This was a person. She made  her  own beer and was kind of stingy with it. This was a person. She was always in a hurry. She had a bunch of tattoos. This was a person. She never ate breakfast. This was a person. She could play banjo. This was a person. He sang at parties. This was a person. He sang. This was a person. She brought great food to social gatherings. She ate a lot of fiber. This was a person. She occasionally shop lifted. This was a person. He didn't get along with animals. He spends a lot of time watching tennis. This was a person. She never finished the book club book. This was a person. She had a lot of Beatles records. This was a person. He  was training to run a marathon. This was a person. She grew up on a farm.  She spent a lot of time with old people. This was a person. She  was a plumber. This was a person. She went to the horseraces. This was a person. He could play harmonica. This was a person. He  only ever had sex with one person. This was a person. She had tropical fish. She prefered bread without crusts. 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. He loved chocolate. This was a person. She snored. This was a person. He loved oreos. This was a person. He had crazy hair colors. This was a person. He was allergic to peanuts. This was a person. She excelled at woodworking. This was a person. She was working  her  way through all of the shows on Netflix. This was a person. He never finished the book club book. This was a person. He  always bought flowers for  his  desk. This was a person. He was an awful driver. This was a person. She  was learning to speak French. She  was a tailor. This was a person. She was kind of addicted to ebay. This was a person. He was thrifty. This was a person. He could play banjo. He ate a lot of raisins. This was a person. She was a cheapskate. This was a person. She has two living parents. This was a person. She  was a mason. She can't watch the end of T2 without crying This was a person. She had a lot of music on vinyl. This was a person. She was gluten intolerant. This was a person. He wrote for the newspaper. This was a person. She abused cars. This was a person. She  always bought flowers for  her  desk. This was a person. He  had VD. This was a person. He  was a tailor. He just had  his car stereo repaired. This was a person. She constantly wore sunglasses. She was a wedding photographer. This was a person. He wore earphones all the time. This was a person. She lived on breakfast bars. This was a person. He spent a lot of time with old people. This was a person. She can't watch the end of T2 without crying She talked during movies. This was a person. She had a twin. This was a person. He  only ever had sex with one person. He  was a translator. This was a person. She ate a lot of hot dogs. She was very good at cleaning. This was a person. He made  his  own beer and was kind of stingy with it. This was a person. He  went to church. This was a person. He played chess. This was a person. She  was learning to use CAD software. This was a person. She was sporty. This was a person. He was 4 days sober. This was a person. She was rebuilding an engine. This was a person. She loved James Bond movies. She loved Elvis. This was a person. She helped strangers. This was a person. She had a baby boy. This was a person. He  only ever had sex with one person. This was a person. She made scrapbooks. This was a person. He wore bow ties. This was a person. He  was afraid of flying. He  was learning to use CAD software. This was a person. He overtipped. This was a person. She loved oreos. This was a person. He has a suit at the cleaners. He helped people. This was a person. She  was a teacher. This was a person. He never drank coffee. This was a person. She had an awesome home theatre. This was a person. He knew how to get free satelittle television. He once robbed a bank. This was a person. She wore Spandex. She spends a lot of time watching tennis. This was a person. He went to the horseraces. He had a lot of shoes. This was a person. He brought great food to social gatherings. This was a person. She  had been having trouble tying  her shoes because  she  pulled a muscle in her abs. She  was a drunk. This was a person. He played piano. He chewed gum constantly. This was a person. He  could always get tickets. This was a person. She  had a hangover yesterday. This was a person. She was an awful driver. She took careful notes after every meal. This was a person. She ate a lot of chinese food. She was the unofficial relationship guru among   friends. This was a person. She could play trumpet. This was a person. She could play trumpet. This was a person. She knew how to get free satelittle television. This was a person. She loved fine dining. This was a person. She was an awful driver. This was a person. He wrote for the newspaper. This was a person. She excelled at woodworking. This was a person. She could fall asleep anywhere. She was the richest of  her friends. This was a person. He was a vegetarian. This was a person. He had just paid a crapload of money to get    teeth fixed. This was a person. She was an expert barbecuer. She had a tiny wine collection. This was a person. She occasionally shop lifted. This was a person. She wore a lot of hats.  This was a person. She plays fantasy football.

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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