[OC] Meistgesehene Personen auf Wikipedia im Jahr 2025 – Wie Katalysatorereignisse das soziale Gedächtnis prägen

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](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 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.

https://preview.redd.it/ycdo5p6x2ajg1.png?width=1581&format=png&auto=webp&s=9702f95de9479a1342f78d57528960097062b1ef

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.