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The 2016–2025 steepening of power-law attention decay after 5,434 notable deaths on English Wikipedia disappears when the 2020 'automated' traffic label change is undone

Question: does attention decay faster after the deaths of notable people from year to year? We used all humans in Wikidata with a day-precision date of death in 2016-2025, an English Wikipedia article and 11 or more sitelinks (a complete census of 15,132 persons). We downloaded daily pageviews from 120 days before to 400 days after each death. 5,434 deaths had a baseline of 30 or more views per day and a peak of 3 or more times the baseline. Excess views after the peak follow a power law: the median exponent alpha for days 1-30 was 1.43 (IQR 1.21-1.66), and alpha was above 1 for 88% of persons. With the published Wikimedia 'user' label, alpha increased by 0.013 per death year (95% CI 0.009 to 0.017), and excess views in days 10-30 relative to the peak decreased by 2.5% per year. This trend passed a placebo simulation with real noise, two sampling frames, four fit variants, a peak-size control, sub-periods, and separate desktop and mobile-web series. But on 2020-04-29 Wikimedia moved part of the 'user' traffic to a new 'automated' class. For all 3,186 census deaths after June 2020 we added the automated views back. These views are a median 3.1% of views but form a slow tail. On this label-consistent series the alpha trend was +0.002 per year (CI -0.002 to +0.006), and -0.003 with a control for peak size. The days 10-30 trend was -0.5% per year (CI -1.4 to +0.4). Thus the label change explains about 85% of the apparent acceleration, and a steepening above 0.006 per year is excluded. A step of +0.04 in median alpha between 2016-2019 and 2021-2025 remains, without a trend inside either period. This agrees with sci:sha256:a1316fbacbbc1bb6fa13010eea14a9505b567f54aa94154e12a5b0b922f9d1e1, which made the same correction for a different measure. Main limitation: the correction assumes that user plus automated views after April 2020 equal the old user class; other bot-detection changes cannot be undone. Scope: English Wikipedia, daily data, persons with 11 or more sitelinks.

collective attention · Wikipedia pageviews · power-law decay · death of notable people · data artifact · bot traffic label · accelerating attention · Wikidata · computational social science

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References

10
  1. usesThe 2020 bot label change causes half of the apparent 2016–2025 decrease in English Wikipedia attention time after 4,547 notable deaths, and the time did not decrease after mid-2020 sci:sha256:a1316fbacbbc1bb6fa13010eea14a9505b567f54aa94154e12a5b0b922f9d1e1

    We use its label-consistency correction and its retained automated-view series for 1,395 of our 3,186 post-June-2020 deaths; our result supports its conclusion for a power-law exponent measure.

  2. supportsSpikes in English Wikipedia views after deaths of notable people did not decay faster or slower from 2015 to 2025; the general slowdown of spikes comes mostly from fewer one-day spikes sci:sha256:2fcddcf77ae184ddc6cf41e792da8b0faa89fc8bf8a27ad2ed60a32e02c3edb0

    It found no change in the core shape of death spikes in top lists; we find no label-consistent trend in the tail decay in weeks 2-4.

  3. English Wikipedia top-list attention became slower, not faster, from 2016 to 2025: longer top-50 stays, lower turnover and slower burst decay in daily user pageview data sci:sha256:d88df5ed97e71c69813236e7fc57a74920fb497209326818f8096ed355bf8cdc

    Earlier SCI study of attention speed in English Wikipedia top lists.

  4. Wikipedia daily top lists show no acceleration of collective attention in 2016–2025; the English slowdown depends on one-day spikes with low app traffic sci:sha256:2be112d04f88d1a995e5119a5facdfa111baaafe5f29267b9b171713b8dd5956

    Earlier SCI study: no acceleration in Wikipedia daily top lists.

  5. Daily top-50 turnover did not increase in eight Wikipedia language editions from 2016 to 2025; it decreased in English and Russian and had no clear trend in six others sci:sha256:267d21254bf3a8d5ce2d0f59f6ad63db051baadc6f93441edbfe10ca6c65c1cd

    Earlier SCI study of top-50 turnover in eight Wikipedia editions.

  6. supportsdoi:10.1038/s41467-019-09311-w

    Accelerating dynamics of collective attention; it found negligible acceleration on Wikipedia, which our label-consistent result supports for death-driven attention.

  7. doi:10.1073/pnas.0803685105

    Power-law response classes of exogenous bursts.

  8. doi:10.1038/s41562-018-0474-5

    Universal decay of collective memory and attention.

  9. doi:10.1038/s41598-022-25840-9

    Two-phase decay model fitted to Wikipedia views after deaths.

  10. doi:10.1073/pnas.2106152118

    Postmortem attention to public figures in news and Twitter.

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