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Luis Villa
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Wikipedia's traffic drop: more on languages and freshness

This article originally appeared on the author's blog on April 22, 2026 under a CC BY 4.0 license.

Second quick post on Wikipedia's pageview decline. The first post looked at ~4,000 career articles on English Wikipedia. This one widens the lens to 5,000 articles across eight major-language Wikipedias and asks a sharper question: which topics are dropping, and is the pattern the same everywhere?

Disclaimer the first

Page views are not the only metric for Wikipedia's impact. So take this with a grain of salt, and think about other ways we have impact (including through serving as a knowledge base for LLMs). Still, it is one important channel by which we fulfill our mission and live our values so I think it's worth exploring even as we know it isn't the end-all and be-all.

Disclaimer the second

I'm trying very hard not to draw conclusions. It's obvious that part of the story is LLMs, and probably the biggest part. But it is also very much a story about social media, and apps, and Google SEO, and and and. If you have questions, find me on social; I'll try to answer or dig more into the data if I can.

TL;DR

Since 2016–2019, aggregate monthly pageviews of Wikipedia's "Vital Articles" are down −26% across eight major languages I sampled (en, es, fr, de, it, pt, ja, ar). The Vital Articles are an imperfect set, but they cover a much broader set of topics than my last sample set, and are widely replicated across wikis. (All of these wikis have at least 80% of the articles, making it more apples-to-apples.)

The decline isn't even across topics. Mathematics, physical sciences, and technology are down 43% to 85%; biographical articles and geography are down less than 10% in half the languages I looked at. The per-topic ordering (which have declined the most or the least) is nearly identical in every one of the eight languages.

Freshness of article content matters, but not as strongly as topic.

What I did (briefly)

With help from Claude Code, pulled Wikipedia's on-wiki Level-5 Vital Articles list – 39,707 articles editorially curated into 11 topic buckets (Arts, Biology, Everyday life, Geography, History, Mathematics, People, Philosophy and religion, Physical sciences, Society, Technology). Sampled 5,000 of them with stratification across buckets. For each article, fetched monthly pageviews 2016-01 through 2026-03 in every major language where a sitelink existed. In the twelve languages where at least 80% of the articles existed, I compared a 2016–2019 pre-LLM baseline window against a 2025-04..2026-03 recent window. I fetched 12 languages, but four of them have major confounders (combinations of network access, embargo, and war, in zh, ru, fa, and uk) so for now I've left them out of the analysis.

Full code and pipeline in the open-source repo under analysis/vital-articles/.

Confirming: decline is widespread

The obvious question after my last post was "what about languages outside English?" Here are monthly pageview trajectories for the 8 non-embargo languages, all pegged so that each language's January 2021 pageview level = 100.

Line chart of monthly pageview trajectories for eight major-language Wikipedias (en, es, fr, de, it, pt, ja, ar), all normalized so each language's January 2021 value = 100; every line ends below 100, with English highest and Spanish/Portuguese lowest

January 2021 is a reasonable anchor because it's past the immediate COVID spike of 2020 but before any plausible LLM effect—ChatGPT launched in November 2022. So this chart is asking "compared to where each Wikipedia was in early 2021, where is it now?"

English is losing the least, which is probably the opposite of what a naive "more LLM exposure → more decline" story would predict. English has huge ChatGPT+Claude adoption, and the best models are tested and developed in English. But en.wikipedia holds up better than any other language in my sample. I can see any number of hypotheses for why this is, but not sure how to test any of them. Spanish and Portuguese are losing the most, both in the 50%+ range.

Decline is topic-specific

So what about by topic? This is view-weighted % change from the 2016–19 baseline to the most recent 12 months, one number per (language × topic) cell.

Heatmap of view-weighted percentage change from 2016–2019 baseline to 2025-04..2026-03, eight language rows by eleven topic columns, with clean vertical bands showing Mathematics/Physical sciences/Technology deep red across every language and People/Geography/History pale across every language

Rows are sorted by each language's overall decline (English at top, Spanish at bottom). Columns are sorted by the topic's mean decline across all eight languages (worst on the left, best on the right).

Read it column by column, and note that every column is basically uniform: Mathematics and Physical sciences are declining heavily in all languages. At the other end, People is holding up pretty well everywhere, same for Geography and History.

If topic behavior varied by language, you'd see scattered speckle across the grid – some languages losing their Biology articles, others their Arts articles, others their People articles. Instead you see clean vertical bands. So an important takeaway, though I don't know why: the per-topic ordering of decline is essentially the same in every language.

Details: what is collapsing; what is holding up

Worst-declining topics (top-3 in every single language):

  • Mathematics: between −48% (en) and −83% (es). Mean across the eight languages: −67%.
  • Physical sciences: between −43% (en) and −85% (de). Mean: −66%.
  • Technology: between −43% (en) and −77% (es). Mean: −59%.

Best-holding topics (bottom-3 in every language):

  • People: between −0.1% (en) and −25.8% (ar). Mean: −13%. In English, German, and French, this bucket is essentially flat. In Italian it's −5.6%.
  • Geography: between −2% (en) and −42% (es). Mean: −22%.
  • History: between +5.5% (en, actually grew) and −58% (es). Mean: −28%.

The middle tier – Biology, Society and social sciences, Arts, Philosophy and religion, Everyday life – falls between those two groups.

Does article maintenance matter?

I was asked by an interested Wikipedian to look harder at article recency. He told me that one theory in the Spanish wiki community is that their articles are not well-updated, and therefore penalized in Google and falling faster than English, and asked me to see what I could puzzle out from that.

So: looking at each language's articles by how recently each one was substantively edited (excluding bot edits, minor edits, and reverted vandalism – just real human content edits), do the fresh articles hold up while the stale ones fall harder? Put differently: does active editing predict traffic retention?

TLDR: this is messy to tease out. At least for the best and worst articles, the answer is "for some languages, yes. For others, barely."

Small-multiples chart, one panel per language, comparing the pageview decline of each language's freshest-10% versus stalest-10% of Vital Articles by substantive-edit recency; English shows the widest gap (freshest −7%, stalest −34%), Japanese shows nearly no gap

The chart shows the decline between each language's freshest-10% of articles and its stalest-10%. Some key observations:

English has the strongest effect by a wide margin. The freshest-10% of English Vital Articles declined only about 7%; the stalest-10% declined 34%. In other words, the least-fresh articles do 24% worse than the freshest. Italian (−19 pp), and French (−14%) show more moderate gaps.

Japanese is an outlier: a 1-percentage-point spread. In Japanese, the freshly-edited articles lost traffic at essentially the same rate as articles that hadn't been substantively touched in years. I don't have a good explanation for this, and I'd be curious whether anyone closer to Japanese Wikipedia's editorial culture has one. (Portuguese and Spanish also eyeball on the graph as flatter, but that's in large part because all their traffic is so far down.)

This is important but not the biggest factor. Probably more detail on this later, but: a pooled multi-variate regression across all languages – controlling for topic, article length, editor count, quality, and article age – confirms that article staleness predicts decline in a real but modest way: staleness explains a slice of within-language variance, not a majority of it. The bigger variance-explainers are still topic and language.

Freshness slows the bleeding but doesn't stop it. Even the freshest articles in every language lost traffic between 2016–19 and now. Active maintenance bends the curve – it doesn't reverse it. English editors keeping articles fresh have protected some traffic; English Wikipedia still lost 15% overall.

Open questions for further investigation

Preliminary multi-variate analysis was not very helpful. In other words, looking at all the data I could easily pull, no factors beyond these three (topic, language, freshness) had a ton of impact. But my stats are very rusty and I'd like to polish that more, and perhaps add in more data sources, before I publish that. If you have suggestions, let me know.

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  • Since editors are good for a big chunk of readership, it may be useful to take edit counts per editor (per language version) into account. Just looking at the drop-off per language, I wonder if there's been a drop-off in editors due to the geopolitical situation leaving people with less time for hobbies as they navigate coping solutions for themselves, their families, and friends. Editing Wikipedia may not be top-of-mind when friends get deported or embroiled in real-world conflicts. It's not just zh, ru, fa, and uk that are affected after major upheavals. In terms of article staleness, it may be useful to compare various articles over time from e.g. Britannica: Wikipedia articles don't cost anything to publish, whereas a printed encyclopedia have to make decisions about notability due to publishing costs. If you gather some data about topics that stay and go from them (especially during war years) it may offer new insights. Jane (talk) 12:45, 22 May 2026 (UTC)[reply]
    • Major events can also strong influence people's cultural preferences. For example, uncertainty about the future and changing life priorities. Also, warfare, including "information warfare" and internet balkanization, various forms of propaganda and counter-propaganda, can negatively impact the functioning of the internet and its communities, the psychological state, and even the mental health of users. --Proeksad (talk) 08:31, 25 May 2026 (UTC)[reply]
  • With regards to non-english versions dropping off faster than english wikipedia, I'm wondering how much of that is due to the increased ease in using machine translation today, with a push of the button in the browser, it will now provide a pretty good translation of the whole webpage, particularly for common languages, and as enwiki is the largest version with the most articles and which in my experience generally has a better quality of articles on general topics (as opposed to topics which would mainly be of interest to specific non-english speaking countries), it is going to be the largest beneficiary, thereby slowing the decline in readership by taking the readership from other language versions. Not sure of a good way to test for that with the tools we have though. Giulio 14:35, 22 May 2026 (UTC)[reply]
    I agree the hypothesis of article low quality. Maybe article size, normalized by that in English, might be a practical proxy for quality. fgnievinski (talk) 11:25, 25 May 2026 (UTC)[reply]
  • I remember a good friend of mine who was a Mathematics major at the time, when I suggested he try contributing to math articles on Wikipedia, saying "I tried, but they're genuinely already all almost perfect and I can't think of anything to change". signed, Rosguill talk 15:48, 22 May 2026 (UTC)[reply]
    Lol. Signed, a math editor. --JBL (talk) 19:25, 23 May 2026 (UTC)[reply]
    I my experience, a large amount is flawed or just missing completely. That is not a criticism of the great work that mathematics editors are doing. GanzKnusper (talk) 11:03, 25 May 2026 (UTC)[reply]
    Perhaps I should ask my friend again for his opinion now that he has a PhD. signed, Rosguill talk 16:12, 25 May 2026 (UTC)[reply]
    @Rosguill: I did actually laugh audibly when I read your first comment, but to give a more serious response: I would be super interested in hearing your friend's updated thoughts. I think the answer of your friend at an earlier stage is very understandable and relateable: for topics that are treated in the undergraduate math major curriculum (so, beyond the level of courses taken primarily by engineering or science or social science students, but not yet so advanced that people don't meet them until graduate coursework) it is indeed the case that it would be hard for an undergraduate math major to make big improvements (and has been for many years). In particular, what those articles often lack is (1) a treatment appropriate for people who are not yet taking the courses where the ideas appear (WP:ONEDOWN), and (2) global structure that gives a comprehensive account of all the facets of some topic. Both of those are very difficult to do, and the second one in particular is enormously hard to produce without a broad perspective than a person just learning about the topic won't realistically have. The situation is different off the beaten track of standard coursework, and in both more and less advanced topics. --JBL (talk) 19:43, 30 May 2026 (UTC)[reply]
    I also laughed because except for the most basic math articles, they are uniformly impenetrable to a lay reader. They rarely explain what technical terms mean and use unlabeled variables with reckless abandon. There is far too much assumed knowledge on the part of the reader to follow what the article is trying to demonstrate. Axem Titanium (talk) 04:08, 7 June 2026 (UTC)[reply]
  • In my personal experience and from what I've heard from friends, it seems that going to a Wikipedia article for math help is more of a desperate attempt where you probably won't learn anything new. Like, going to the Wikipedia article on the Normal Distribution will likely not teach the average AP Statistics student anything about the normal distribution, and likewise for most math articles. So my conclusion is that people are no longer visiting the articles that didn't help them in the first place (math) while still visiting the articles that have content understandable to laypeople. Qoiuoiuoiu (talk) 17:13, 22 May 2026 (UTC)[reply]
    There is a reason for that shortcoming though. Wikipedia is not a textbook and will not explain how to learn a skill in math. It will exposit what the subject is, which in the vast majority of fields has significant overlap with learning the subject. However, math is one of the few subjects I would argue textbooks trump encyclopedias pretty handily due to the fact that textbooks act more akin to tutorials. ✶Quxyz✶ (talk) 20:29, 23 May 2026 (UTC)[reply]
  • "He told me that one theory in the Spanish wiki community is that their articles are not well-updated, and therefore penalized in Google". A person attempts to update the article → their version of ClueBot reverts productive edits (latest example) due to its inappropriate configuration causing articles to remain outdated / admins abuse their power as they don't have real counterweights against their actions forcing people not to edit the website → Google is doing us some dirt! Tbhotch (CC BY-SA 4.0) 17:49, 22 May 2026 (UTC)[reply]
    I recently experienced both of these things on Spanish wiki! I was wondering if I was just unlucky. GanzKnusper (talk) 10:34, 25 May 2026 (UTC)[reply]
    Same for the Portuguese Wikipedia. It's a very hostile and toxic environment for non-admin editors. fgnievinski (talk) 11:28, 25 May 2026 (UTC)[reply]
  • I suspect your edit-freshness angle is more closely representative of "is it in the news" (such as celebrity coverage or current events) which tends to raise both pageviews and new edits on any Wikipedia.   ▶ I am Grorp ◀ 21:41, 22 May 2026 (UTC)[reply]
  • No great insights, but many thanks for doing this! I think the possibility of rapid translations may explain why Spanish and Portuguese in particular do so badly. Johnbod (talk) 03:09, 23 May 2026 (UTC)[reply]
  • Thank you Luis for this most interesting article. Obviously, dependance on topic is actually a dependance on the level of difficulty. LLMs‘ answers come with explanations, examples, and q&a. —MBq (talk) 06:12, 23 May 2026 (UTC)[reply]
  • The impact of maintenance is difficult to assess. If an article is rarely edited, the information becomes outdated, and readers/search engines consider the information outdated and uninteresting. But if an article is unpopular, it may be edited less frequently.--Proeksad (talk) 08:31, 25 May 2026 (UTC)[reply]
  • The data here has me wondering whether LLMs are replacing the "looking up a fact"-type use of mathematics articles. When I was a student and I didn't have any books of my own I would use Wikipedia for e.g. comparing the different types of convergence of random variables, or the various ways to define a Polish space, or whatever. And doing a quick test now, GPT-5 mini does a good job at both of those. GanzKnusper (talk) 11:12, 25 May 2026 (UTC)[reply]
    Or maybe what I have just said is true for all areas, but mathematics articles get fewer readers for other reasons, so are more affected. I'm just throwing out random ideas now! GanzKnusper (talk) 11:13, 25 May 2026 (UTC)[reply]
    Like said above, articles on mathematics are not really designed to teach people how to do maths but instead explain what the maths are. It is a small difference but it makes it harder to understand if one is trying to learn the former. That issue is probably then exacerbated by LLMs and media like YouTube and Khan Academy. ✶Quxyz✶ (talk) 13:11, 25 May 2026 (UTC)[reply]
  • Couple of thoughts:
- Any ideas why the big dive down for Arabic?
- It'd useful to know how long we have before irrelevancy - how many years before each language version reaches 10% normalized viewership?
- We should assess the impact of Wikipedia on LLMs. For example, if you ask a LLM for the definition of a bunch of the vital article topics, how many results quote Wikipedia or link to Wikipedia?
fgnievinski (talk) 11:38, 25 May 2026 (UTC)[reply]
  • Honestly, as others have said, the fact that the decline seems focused on heavily technical articles makes me suspect that part of the reason is because those articles are often impenetrable to people who lack a background in the subject (which is most people.) Because of this, they'd prefer even a potentially flawed LLM summary. In comparison, our articles on eg. history or bios are well-written and readable, probably moreso than any LLM summary could be. Though, another possibility is that people are more likely to read history and bios for fun - if someone is searching up a technical question, they probably just want the answer, and are likely to stop when Google's AI puts it at the top of the page. Whereas someone searching for a historical figure or event is more likely to be actually looking for a longform article on it and therefore less likely to be satisfied with a quick AI blurb. --Aquillion (talk) 15:07, 28 May 2026 (UTC)[reply]
    Could we make science fun on Wikipedia? ✶Quxyz✶ (talk) 15:11, 28 May 2026 (UTC)[reply]
    That would require both expertise and ability to elegantly simplify and clarify even abstract and technical topics. It can be done, I recently leafed through the World Book Encyclopedia and can say that as a math layman I managed to build a very basic image of some mathematical topics and find some mental "place" for them, which is quite enough for someone who will never have to make use of that knowledge, thanks to the simple definitions (that real mathematicians would probably find useless or unsatisfying) and clear examples with plain-language explanations. As Aristotle already noted in Poetics, learning is fun by itself. The only problem that has to be solved by people is to find out how to learn/teach, because if you don't understand what you're reading (it's too far above your level of understanding) you're not learning and not having fun.
    And let's be honest, some of the "technical" style on Wikipedia is just bad writing and isn't necessarily inherent to encyclopedias. Articles on mathematics can't teach us math, but how come the same topics are treated so much more clearly and layman-friendly in traditional encyclopedias? It's not just the scientific articles that can suffer from this, here's a really bad case from linguistics:
    Linguistic purism or linguistic protectionism is a concept with two common meanings: one with respect to foreign languages and the other with respect to the internal variants of a language (dialects). The first meaning is the historical trend of the users of a language desiring to conserve intact the language's lexical structure of word families, in opposition to foreign influence which are considered 'impure'. The second meaning is the prescriptive practice of determining and recognizing one linguistic variety (dialect) as being purer or of intrinsically higher quality than other related varieties.
    Compare this to the definition in R.L. Trask's Language and Linguistics: The Key Concepts:
    PURISM: The belief that words (and other linguistic features) of foreign origin are a kind of contamination sullying the purity of a language.
    While Trask's definition doesn't cover everything that can be covered by the term in practice, it does provide the central meaning. A respected linguist believed that this imperfect definition is good enough to write down, and countless students and laymen will find it immediately useful and applicable. Wikipedia's current definitions on the other hand are a jargon-laden word salad that's not even particularly accurate (it's a belief, as Trask says; it's not a trend, and not necessarily historical). Props to the editors who have recently tried to improve it, but IMO it should just be deleted and rewritten from the ground up.
    But Wikipedia doesn't have lots of experts of Trask's caliber...
    Phazd (talk|contribs) 06:38, 29 May 2026 (UTC)[reply]
    Though, another possibility is that ... if someone is searching up a technical question, they probably just want the answer, and are likely to stop when Google's AI puts it at the top of the page. Yes, this is the explanation (sorry haters). Various technical question-answer sites (MathOverflow, etc.) are also experiencing massive declines in views, for the same reason. Essentially no one anywhere has ever pleasure-read technical writing; reading well written work on technical subjects is hard work. --JBL (talk) 19:48, 30 May 2026 (UTC)[reply]
  • I'm semi-decided about the quality of mathematics coverage, LOL – need more expertise to help me decide – wbm1058 (talk) 13:14, 9 June 2026 (UTC)[reply]

















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