We measure how the world's news covered people being harmed — and the help and hope within it.
113 of its 156 stories (72%) were about people being harmed, usually 28%. Jammu accounted for 90 of Kashmir's 113 stories about harm, carried by 40 outlets. Reports of people injured ran at more than ten times the usual rate (81 stories). Its coverage was about three times as grief-stricken as the world's.
57 of its 146 stories (39%) were about people being harmed, usually 25%. Reports of people affected ran at about 6 times the usual rate (35 stories). Landslides were named in 34 of its stories about harm, more than ten times usual, with heavy rain. Its coverage was about twice as grief-stricken as the world's.
33 of its 106 stories (31%) were about people being harmed, usually 16%. Stockholm accounted for 25 of Sweden's 33 stories about harm, carried by 37 outlets. Reports of people injured ran at more than ten times the usual rate (15 stories).
7 of its 10 stories (70%) were about people being harmed, usually 9%. 4 of Skopje's 4 stories were about protests or strikes. Reports of people injured ran at more than ten times the usual rate (7 stories).
32 of its 72 stories (44%) were about people being harmed, usually 16%. Buenos Aires accounted for 23 of Argentina's 32 stories about harm, carried by 35 outlets. Reports of people injured ran at more than ten times the usual rate (22 stories).
73 of its 177 stories (41%) were about people being harmed, usually 28%. Kyiv accounted for 48 of Ukraine's 73 stories about harm, carried by 71 outlets. Its coverage was about one and a half times as angry as the world's.
22 of its 87 stories (25%) were about people being harmed, usually 11%. Reports of people displaced ran at more than ten times the usual rate (10 stories). Its coverage was about one and a half times as warm as the world's.
19 of its 70 stories (27%) were about people being harmed, usually 12%. Reports of people injured ran at more than ten times the usual rate (13 stories). Tornadoes were named in 12 of its stories about harm, more than ten times usual.
62 of its 139 stories (45%) were about people being harmed, usually 25%. Reports of arrests ran at about 5 times the usual rate (17 stories).
27 of its 49 stories (55%) were about people being harmed, usually 31%. Outbreaks were named in 16 of its stories about harm, more than ten times usual, with ebola.
Also named far more than usual: outbreaks in Ethiopia (16 of its stories, more than ten times its usual); tornadoes in Portugal (12 of its stories, more than ten times its usual); extreme cold in UK (26 of its stories, more than ten times its usual); landslides in US (45 of its stories, about 7 times its usual).
Stories about people being harmed, in every 100 stories, the 30 days to 15 Nov. 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 9,167 stories about harm among 60,273 counted on 15 Nov.
In Kashmir, 72% of the news was about people being harmed, where 28% is usual. Stories about people being harmed made up 15 in every 100 of the day's 60,273 stories, below the usual 16. A year earlier, on 15 November 2024, 17 in every 100 stories were about people being harmed, against 15 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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