Did you ever have a situation where you were making something, and early on in the process you realized you had to make something else in order to finish what you were originally working on?
I ran into that over the weekend, but the something else I made was so much fun to play with I decided to put it up as its own Search Gizmo. The Wikipedia Page Count Checker is available at https://searchgizmos.com/wpcc .
I’m sure there are other tools out there that let you chart Wikipedia page views, but I wanted to make sure I had a good grip on the Google Charts API. Just enter a Wikipedia page topic (WPCC checks that page and finds the closest match, so it’s somewhat forgiving of spelling errors, etc) and the date you want your pageview count to start. You can chart up to 30 days.
Here’s how the Dolly Parton example search looks:
The chart isn’t an image – it’s dynamic so you can hold your mouse over a point on the chart and get specific information.
The Dolly Parton example is interesting, but I find searches related to specific events to be more interesting. For example, Angela Lansbury died on October 11. Here is a look at her Wikipedia page over a 10 day period starting October 8th:
Festivals and other multi-day events have a less dramatic peak, but they’re still evident in page view counts. This is a chart of Lollapalooza’s page views starting on July 25 and going for 10 days.
Of course, if you DO want drama, try looking at the counts for something that happened on live television or in some other way where many people heard about it at the same time. Here’s what Will Smith’s Wikipedia page counts did right before and after the slap heard ’round the world:
Chris Rock’s Wikipedia page views experienced a pretty crazy trajectory too!
As I noted at the beginning of this article, I made the WPCC because I needed it for something else I was making, and as you can see it’s not very polished. But now that I’ve played with it some I wonder if there’s more I can do with it.
Should I add the capacity to chart multiple people at a time? Expand the timespan past 30 days? Drop a comment if you want to see me put a little more into this one.
Categories: RB Search Gizmos
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Just kind of curious: what’s the limiting factor that maxes out the day count at 30? Is it API-imposed or more like a performance thing? How difficult/impossible would it be to open the window to a year’s worth of results?
I was thinking about how an author or other public figure could get a quick handle on interest surrounding a recent (or otherwise) work with an identifiable timeline — like publication date for a book, or release date for a film or TV series, or posting date for a music video, etc. Tried it with author V.E. Schwab, during the 15 days before and after publication of ‘The Invisible Life of Addie LaRue,’ and also for ‘The Sandman’ during the month the Netflix series was released. There were the expected spikes in interest…
…but still, I was curious what the spikes, y’know, MEAN. For instance: presumably, Wikipedia is used by people who don’t already know [whatever] about [the subject in question]. So there’d be a ‘pedia-usage spike on that topic during a period when the topic was in the news, say. But it would tell us only about interest among the previously less-informed general public. So, then, would it be possible to somehow triangulate the Wikipedia usage with some other source of data — viewership, YouTube hits, whatever — to produce a more finely-grained view of public interest? (Of course I’m talking like I know what I’m talking about!)