Fame half-life

The dataset

Look up anyone in the dataset

Every person here died, or won a Nobel Prize, an acting or directing Oscar, the Ballon d'Or or the Booker Prize, between January 2016 and October 2025. Pick one to see their daily views from 60 days before to a year after, the baseline, the fitted decay and the half-life.

Live

Try any Wikipedia article

Type any English Wikipedia article title. Your browser asks Wikimedia for the article's daily views since July 2015 and fits the same three curves here, in the page. Leave the date empty to use the busiest day on record.

The fade

Most of the spike is gone within a week

On the median death the page draws 206 times its usual traffic on the peak day, which is the day after the death in 44% of cases. Smoothed over a week, half the extra traffic is gone 2 days after the peak (middle half 2 to 3 days). The averaged curve loses nine tenths of its excess in 5 days and sits at 1.96 times baseline a month later and 1.09 times in the last month of the year, before jumping to 1.58 times on the anniversary. Awards lose nine tenths in 4 days, and climb again in the last week of the year as the next prize comes round.

1,839 of 1,905 deaths have a visible spike (peak at least twice the baseline) on days 0 to 3. Another 65 (3.4%) have a delayed spike: nothing on days 0 to 3, then a day above twice the baseline on days 4 to 30 (Leonard Cohen, Sam Shepard and Steve Ditko among them), most often because the death became news days or weeks after it happened. 1 death has no spike at all.

The curve

A fast fade and a slow tail fit most events

Each event's daily views after the peak were fitted three ways, with every day counted: the baseline plus an exponential decay, plus a power law, or plus a biexponential (two exponentials, the form Candia et al. 2019 found over years in attention to songs, films and biographies). The biexponential has the lowest AIC for 76% of 1,839 deaths and 64% of 177 awards; the power law wins 14% of deaths and the exponential 9%. Where the biexponential wins, its fast part has a median time constant of 3.0 days and carries all but 1.8% of the initial excess; the slow part's median time constant is 169 days. On simulated series the selector names the true model 87% of the time for a pure exponential, 95% for a power law and 100% for a biexponential, and it calls 13% of pure exponentials biexponential, so the real share is a mild overstatement.

The aftermath

A death leaves a page a little busier than before

A year after a death the median page draws 1.08 times its old traffic, and 59% of pages sit above their baseline. Award winners settle at a median 4.20 times, but the prizes differ: Nobel laureates, with a median of 20 views a day beforehand, keep 8.81 times that; Booker winners 2.56; Ballon d'Or winners 0.87. For Academy Award winners the answer depends on which 'before' you use: against the 53 days ending a week before the nominations it is 0.58, against days -150 to -90 before the ceremony 1.03. Among deaths, each extra year of age at death goes with 2.0% less lift (p < 0.001), and pages that were busier beforehand gain less.

Who lasts

Which prize matters more than what the person did

Among deaths, the share of the first year's extra views that arrive after the first week runs from 23% (business) to 33% (writing and journalism), and median lift from 0.97 times (business) to 1.22 times (music). The gap between Nobel and Oscar winners is wider than any gap between occupations.

Corrections

What changed on 29 October 2026

Corrected 29 October 2026, after an independent audit. Three 2022 Nobel laureates in economics were missing because the Nobel Prize API gives the wrong year for that prize; they are now in. The curve comparison published on 28 October fitted only days above the baseline, which made a biexponential win almost by default (it reported 90%); every day now counts, and the selector was checked on simulated data. The half-life compared a smoothed series with a single raw day; it now compares like with like. 65 deaths reported days late are counted as delayed spikes rather than no spike. The Oscar baseline fell after the nominations; it now ends a week before them. Earlier figures are kept as sensitivity rows. Every change is listed in docs/decisions.md.

Limits

What this cannot show

• English Wikipedia only. A view is someone looking a person up, which is not the same as caring about them.
• The fame floor of 30 Wikidata sitelinks decides who counts as famous and leans toward people known in many countries. It is today's count, so some people clear it because of the death itself.
• Some automated traffic passes the user filter. Capping any day above 50 times its neighbors touches 31 events and leaves every half-life unchanged.
• A death or an award can coincide with other news about the same person, such as a film release or a scandal, and nothing in the data separates the two.
• Awards season raises an Oscar winner's traffic for months, so any "before" window is a choice. The baseline here ends a week before the nominations (median 9,378 views a day); the spec's window, after the nominations, gives 15,119, and days -150 to -90 before the ceremony give 5,641. The Oscar lift is 0.58, 0.38 and 1.03 on the three.
• The half-life as the spec first defined it compared a 7-day average with the single peak day, so it came out at one day for 95% of deaths. It now compares the smoothed series with its own smoothed peak (median 2 days); the old measure stays in the sensitivity table.