We measure how the world's news covered people being harmed — and the help and hope within it.
356 of its 706 stories (50%) were about people being harmed, usually 38%. Buner accounted for 118 of Pakistan's 356 stories about harm, carried by 323 outlets. Reports of evacuations ran at about 5 times the usual rate (27 stories). Helicopter crash was named in 19 of its stories about harm, more than ten times usual. Its coverage was about twice as grief-stricken as the world's.
303 of its 946 stories (32%) were about people being harmed, usually 24%. Reports of arrests ran at about twice the usual rate (91 stories). Its coverage was about one and a half times as warm as the world's.
Reports of people injured ran at about three times the usual rate (11 stories). Earthquake was named in 28 of its stories about harm, more than ten times usual, with tsunami and power cuts. Its coverage was about one and a half times as fearful as the world's.
Gaza accounted for 91 of Palestine's 125 stories about harm, carried by 184 outlets. Reports of evacuations ran at about 6 times the usual rate (13 stories). Its coverage was about twice as angry as the world's.
89 of its 137 stories (65%) were about people being harmed, usually 44%. Kishtwar accounted for 55 of Kashmir's 89 stories about harm, carried by 34 outlets. Reports of people affected ran at about 5 times the usual rate (41 stories).
15 of its 23 stories (65%) were about people being harmed, usually 18%. Reports of people injured ran at more than ten times the usual rate (13 stories). Its coverage was about one and a half times as grief-stricken as the world's.
Jerusalem accounted for 86 of Israel's 283 stories about harm, carried by 224 outlets. Reports of evacuations ran at about twice the usual rate (9 stories). Its coverage was about twice as angry as the world's.
31 of Toronto's 50 stories were about protests or strikes. Reports of people affected ran at about three times the usual rate (96 stories). Train derailment was named in 11 of its stories about harm, more than ten times usual.
14 of its 19 stories (74%) were about people being harmed, usually 17%. Tropical storm was named in 10 of its stories about harm, about 4 times usual.
32 of its 107 stories (30%) were about people being harmed, usually 16%. Reports of people injured ran at about 7 times the usual rate (6 stories).
Also named far more than usual: tropical storm in U.S. Virgin Islands (10 of its stories, about 4 times its usual); tropical storm in US (152 of its stories, about 5 times its usual); train derailment in Canada (11 of its stories, more than ten times its usual).
Stories about people being harmed, in every 100 stories, the 30 days to 16 Aug. The big dot is this day; the shaded band is a normal day (the 30 days before it). Click a day to open it. Based on 9,259 stories about harm among 49,148 counted on 16 Aug.
Mentions of tropical storm ran about 4 times their usual in the U.S. Virgin Islands' news. of the day's 49,148 news stories, 19 in every 100 were about people being harmed, as usual. Pakistan stood out: 50% of its news was about people being harmed, usually 38%. A year earlier, on 16 August 2024, 19 in every 100 stories were about people being harmed, the same as today.
Written by code from the day's numbers.
Countries with at least 50 stories that day.
Stories, not people.
The day's biggest events: attacks, accidents and disasters, people displaced, protests, outbreaks. Bigger dot: more stories. Ranked by the share of the day's outlets that reported it and how clearly it was about one thing, the same way for every place and year; the news data does not say who attacked whom, so both sides of a war appear where the news put them. Click a dot for its stories.
Of the stories about people being harmed, what part of life each was about. The mark is usual.
Stories that report it, not people: we count what reporters wrote, not what happened.
The words in the day's stories were about as usual. Filled dot: today. Ring: usual.
From the words reporters used across the whole day, never one story. Fear is the weakest of the four measures. How?
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