An interesting conversation in the comments to Cole Camplese‘s post about the importance of having access to data in a university system. Brett Bixler brought up the idea of bringing some game aspects to using the data, and Cole pushed toward the ‘how many clicks’ game:
students are given a random starting topic and a random ending topic and they have to see how many clicks through articles it takes to get from A to B … an example might be, “get from the topic iPod to Kennedy Space Center.” I wonder if we could design something like that uses tag aggregation as a pass through
I’d love to see something like that, might even scrape up the time to work on something like that, but need help figuring out what, exactly, that might look like. Tags might be a great way to start something like this off. Links might be a way, too. How does the game work, though? I don’t really know where to begin with this.
One additional thought. Theoretically, with both tags and links we could come at it from two different directions. One is to have something that focuses on the existing tags/categories and links to make the game go. The other is for players to create their own links and tags/categories on posts they encounter. Since the data in SemanticUMW is in a completely separate database from the UMWBlogs database, this could fairly easily be done, and might even provide an additional set of interesting and useful data.
Anyone with ideas/models for sharpening up this fuzzy idea?
After I posted this morning about the number of posts by hour on UMWBlogs, Jim reposted it, and from there D’Arcy Norman at UCalgary did similar digging in his WPMU tables. Since he’s working directly from the database, he could even dig out stats for comments, something that I’m unable to do.
One thing that really struck me was how similar the posts-by-hour data was between UCalgaryBlogs.ca and UMWBlogs.
Again, posts by hour at UMWBlogs:
And at UCalgary:
That got me wondering if the data that D’Arcy grabbed about posts by day would be similar. Close, but a little different:
Looks like at UMW we can’t get ourselves back into the blogging mode after the weekend until Tuesday, while the Canadians come out swinging on Monday!
Hopefully, as more and more campus-wide blogging platforms come up, we’ll be able to compare this kind of data across a lot of institutions. I don’t know what might pop out of it, but it should be interesting. (BTW: Cole Camplese wrote just today about the question of why to run a service in-house instead of outsourcing to an external service. What we have here is just another example of his argument–because when its in-house we can get at the really interesting underlying data.)
If nothing else, I think this can start to give some real insights into how students are living their lives, at least in a very broad sense. Along those lines, here’s the parallel data that I fantasize about having:
- Library patronage
- Library book checkouts
- Wikipedia readership
- Beer consumption
- TV watched
- Homework time
- Pleasure reading
Anything more that you all would like to do the comparisons on? Not that there’s any chance that I can actually dig all this up. I’m just sayin’ the comparisons would be interesting.
Tis now the very blogging time of night
When posts do churn and the bava breathes out
Edupunk to this world . . .
(Apologies to Shakespeare)
Over the weekend there was an odd glitch with the scrapers. They’re still down until we figure out exactly what’s going on, so unfortunately I might miss some of the blog data from over the weekend.
But it brought up the interesting question of, if I need to test something, when is it lease likely that people will be posting to UMWBlogs. Of course the intuitive guess is “late at night”. But I’ve got data, so let’s use it.
Here’s a table and simple bar chart of how many posts were written when. NB — many posts get aggregated and republished, which means that they show up in this data twice. Alas, I don’t have a good mechanism for tidying up the data there.
Looking at 16877 posts, for you folks who like that kind of stuff.
|12am – 1am
|1am – 2am
|2am – 3am
|3am – 4am
|4am – 5am
|5am – 6am
|6am – 7am
|7am – 8am
|8am – 9am
|9am – 10am
|10am – 11am
|11am – 12pm
|12pm – 1pm
|1pm – 2pm
|2pm – 3pm
|3pm – 4pm
|4pm – 5pm
|5pm – 6pm
|6pm – 7pm
|7pm – 8pm
|8pm – 9pm
|9pm – 10pm
|10pm – 11pm
|11pm – 12am
Blogging Times chart
I was actually a bit surprised by how late into night people are blogging — I expected it to taper off a little earlier. I’m also curious about the dip right at 5 and 6 pm. Is that just dinner time? If so, it might be interesting that our blogging practices are so closely tied to that social norm.
And it looks like if I’m going to be testing things, I’ll need lots of coffee.
Today, the scrapers scraped in their 15000th post from UMWBlogs. Way to go to everyone at UMW using it!
To celebrate, I’m also ready to finally add some better design and style to the exhibits. Thanks to the hard work and many tears that I caused her, our student aide Serena Epstein has added a prettiness to the exhibits that I would never have been able to accomplish. Thank you Serena!