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.
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.
ErasedAstronaut on
What classifies a page view? Is it just the name of the individual, or does it also included wiki pages that are related to the individual?
For example: “Charlie Kirk” vs “Charlie Kirk” + “Assassination of Charlie Kirk”
Doesntmatter1237 on
Damn who is rob reiner? Don’t hate me I’m actually asking
bluegardener on
This is how I find out they made a show about ed gein last year.
![[OC] Most-Viewed People on Wikipedia in 2025 - How Catalyst Events Imprint Social Memory](https://www.byteseu.com/wp-content/uploads/2026/02/8ayzd6kz1ajg1-919x1536.png "[OC] Most-Viewed People on Wikipedia in 2025 – How Catalyst Events Imprint Social Memory")
5 Comments
What is social memory? Struggling to understand what that metric is telling me sorry
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 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.
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.
What classifies a page view? Is it just the name of the individual, or does it also included wiki pages that are related to the individual?
For example: “Charlie Kirk” vs “Charlie Kirk” + “Assassination of Charlie Kirk”
Damn who is rob reiner? Don’t hate me I’m actually asking
This is how I find out they made a show about ed gein last year.