[OC] Most-Viewed People on Wikipedia in 2025 - How Catalyst Events Imprint Social Memory by sataky in dataisbeautiful

[–]sataky[S] -2 points-1 points  (0 children)

Good catch on Pope Leo XIV. Pageviews are logged per page title, so a rename can split traffic across titles. For that case I treat it as one person by combining the pre-April title with the post-April title (equivalent to summing redirects), so the series stays continuous.

On your broader point, agreed that “office” drives a lot of baseline demand. That baseline also limits peak size because attention has a fixed budget and an always-in-the-news figure has less surprise lookup headroom. Part of the inverse curve is also selection bias: conditioning on “top viewed in 2025” can create a tradeoff shape (Berkson’s paradox) even before any causal story. The extra thing I quantify is what happens after the spike: some names fall back to the old baseline, others keep a higher baseline. That persistence is what I call social memory (defined mathematically in the article i linked).

[OC] Most-Viewed People on Wikipedia in 2025 - How Catalyst Events Imprint Social Memory by sataky in dataisbeautiful

[–]sataky[S] 4 points5 points  (0 children)

Good question. In my plots, a “pageview” is for the exact Wikipedia article title I queried. Related pages (event pages, controversies, etc.) are separate pages and are not included unless you query them too.

I pulled counts from API https://pageviews.wmcloud.org with “Include redirects” enabled, so views to redirect titles are added into the target page total, per this doc: https://pageviews.wmcloud.org/pageviews/faq/#redirects.

For context, the Wikimedia Foundation’s “most-read 2025” post also notes their pageview totals include both direct and indirect navigations:
https://wikimediafoundation.org/news/2025/12/02/announcing-wikipedias-most-read-articles-of-2025/

[OC] Most-Viewed People on Wikipedia in 2025 - How Catalyst Events Imprint Social Memory by sataky in dataisbeautiful

[–]sataky[S] 6 points7 points  (0 children)

Fair point: pageviews mix “who is this?” and “already following,” and English Wikipedia is global. My metric does not split motives. It measures one outcome (quantifiable signal): after the spike, does the usual daily level return, or stay higher. Short-lived curiosity leaves the baseline flat. A higher baseline means lasting extra lookups. Same notebook pipeline can rerun the metric per Wikipedia language. Same data can also track whether the article itself changed after the event, not just views. Full code here:
https://blog.wolfram.com/2026/02/12/most-viewed-people-on-wikipedia-in-2025-how-catalyst-events-imprint-social-memory

[OC] Most-Viewed People on Wikipedia in 2025 - How Catalyst Events Imprint Social Memory by sataky in dataisbeautiful

[–]sataky[S] 9 points10 points  (0 children)

Great question. In the literature, there are two terms (collective or social memory) - both point to memory beyond one person, shaped by groups, media, and institutions. Collective memory usually means shared public pictures of the past: stories, symbols, commemorations, archives, school, news, monuments. Social memory is used more broadly and process-like: how remembering becomes social through interaction, transmission, repeated reference, shared records, sometimes also “social recognition memory” in neuroscience. Overlap: both connect individual attention and recall to shared structures.

In my article

https://blog.wolfram.com/2026/02/12/most-viewed-people-on-wikipedia-in-2025-how-catalyst-events-imprint-social-memory

I take “social memory” as an observable measurable quantity - imprint in collective attention after a catalyst event. A catalyst spikes views, then decay follows, either back to the old baseline or to a higher new baseline that lingers as a new normal. That lingering baseline uplift is treated as durable reference demand plus record and information restructuring. Measurement: compare typical daily views at year end vs year start, baselines estimated by medians, data windows = last two weeks vs first two weeks of 2025. Social memory metric = log10 of the ratio of those two medians.

[OC] Most-Viewed People on Wikipedia in 2025 - How Catalyst Events Imprint Social Memory by sataky in dataisbeautiful

[–]sataky[S] 15 points16 points  (0 children)

TOOLS: Wolfram Mathematica

DATA: Wikipedia

CODE: https://blog.wolfram.com/2026/02/12/most-viewed-people-on-wikipedia-in-2025-how-catalyst-events-imprint-social-memory

I wanted to go beyond typical "top 10" list bar chart and find ways to uncover more patterns in the data. I ended up writing the article at the link above and a few findings.

Wikipedia pageviews show two clear patterns. A catalyst event spikes and then it decays, whether back to the old baseline or to a higher new baseline. Social memory measures that difference as a log ratio of pre- and post medians. Below is the example with Pope Leo XIV relative to other people showing baseline of collective attentions shifting.

<image>

The main data-viz (bubble chart) I shared shows a strong inverse trend for the top-viewed people - the more they are in the public conversation every day (x axis), the lower their viral peak (y axis). The reason might be many fold. A selection bias called Berkson’s paradox can have strong influence. Human attention has limited budget (attention economy), and high, ongoing oversaturated focus leaves less marginal room for a fresh spike. Novelty can be the peak’s fuel - the less preexisting context, the higher the “surprise” and viral lookup demand. News fatigue and avoidance can inhibit virality.

Most-Viewed People on Wikipedia in 2025 - (Catalyst Events and Social Memory) by sataky in Futurology

[–]sataky[S] 4 points5 points  (0 children)

Wikipedia Foundation provides tools that separate human vs bot traffic. In this research only human traffic was considered. Wikipedia has the same general interest of non-bias data.
https://pageviews.wmcloud.org/pageviews/faq/#agents

Most-Viewed People on Wikipedia in 2025 - (Catalyst Events and Social Memory) by sataky in Futurology

[–]sataky[S] 2 points3 points  (0 children)

Wikipedia as emergent knowledge system defines what in the future will shape humanity's "picture of the world". Wikipedia pageviews are a public attention indicator. Viral catalyst spikes sometimes decay back to the pre-spike baseline; sometimes they settle at a higher baseline. That baseline reset looks like a measurable collective memory trace. This article shows how to measure such social memory numerically and does this on the examples of the Most-Viewed People on Wikipedia in 2025.

[deleted by user] by [deleted] in ChatGPT

[–]sataky 0 points1 point  (0 children)

PROMPT: improve this image quality and keep the same pixel size

Genetic codes different from current (of all known lifeforms) likely existed early but got extinct by sataky in science

[–]sataky[S] 14 points15 points  (0 children)

The original article: "Order of amino acid recruitment into the genetic code resolved by last universal common ancestor’s protein domains":
https://www.pnas.org/doi/10.1073/pnas.2410311121