86.2% of the Classifiable Pages Among English Wikipedia's 100 Most-Read Are Now About People, News Events or Entertainment, Up From 77.0% in 2022

Summary

Picture a local news site and a local history blog that both used to get steady traffic from people looking things up. The news site still gets spikes when something happens. The history blog's evergreen pages have gone quiet. The pattern at the very top of Wikipedia is similar.

We looked at English Wikipedia's 100 most-read articles each year since 2022 and classified each one by hand by type. In the past 12 months, 86.2% of the pages we could classify were about people, news events or entertainment. In 2022 it was 77.0%. Evergreen reference topics, such as countries, platforms and major historical subjects, made up a shrinking slice.

The top of Wikipedia also turns over faster. More articles pass through the monthly top 100, and most of them stay for a single month. Readers still come to Wikipedia for what is new. They appear to come less often for what an AI answer can summarize.

What we measured

For each 12-month period we ranked English Wikipedia articles by desktop plus mobile web views and took the top 100. We hand-classified every page into people, news events and sport, entertainment, or evergreen reference. Pages that showed signs of automated traffic (for example a page at the top every year with no news reason), adult pages and Wikipedia's own pages were set aside; 12 to 14 per year.

We also ranked articles every month and counted how many different articles reached the top 100 and top 1,000, and how many months each stayed. Labels were assigned by hand. Historical figures count as people.

News, people and entertainment took over the top 100

Make-up of English Wikipedia's 100 most-read pages (excluding suspected automated, adult and meta pages):

The evergreen pages that remain are mostly countries and the biggest websites and apps. Reference topics that people used to look up out of curiosity have dropped out.

Evergreen pages now get a smaller share of top-100 reading

Share of top-100 views by type:

The drop came in 2024, the year AI Overviews launched in the US, and has not recovered.

The top of Wikipedia turns over faster

Monthly turnover in the top 100 and top 1,000:

More articles pass through the top lists and each stays for less time. Attention on Wikipedia is driven more by what is happening this month than by topics people return to.

What this means

For a business blog, the lesson is that timely content still earns attention, while evergreen explainers are the content AI answers absorb first. That does not mean dropping evergreen pages. In AI search optimization, those evergreen pages work as source material that AI answers quote. What it does mean is adding a steady flow of timely, specific content: seasonal advice, local news, new products, recent projects and answers to questions customers asked this month.

Keep evergreen pages accurate and clear so AI tools can cite them, and use timely content to give people a reason to visit you directly. Not sure which pages AI already draws on? A free AI visibility audit from our AI SEO agency will tell you.

Limits

Wikimedia pageview counts include some automated traffic that its filters do not catch, and Wikimedia changed how it detects bots in 2025, which lowers counted views from that point on. Some of the change in any period may reflect better bot filtering rather than fewer human readers.

We count views of titles that had at least 5 views in a given month on a given site, which drops a very small tail of rarely read pages.

Classification is manual, and some pages could fit more than one type; historical figures are counted as people.

12 to 14 pages per year were set aside as suspected automated traffic, adult content or meta pages. Including them would not change the trend but would change the counts.

Annual top-100 lists favor long-running stories; monthly lists capture short spikes.

Frequently asked questions

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