Content contributors, statistical analysis Options

[Peter Damian]

My blog post for today http://ocham.blogspot.com/2011/10/repetiti...-wikipedia.html on whether there are statistically measurable properties that distinguish 'content contributors' from wiki-gnomes. Conclusion: the statistical difference is strongly indicative of a real difference, discussed in detail on the blog.

Remaining questions: why do content contributors remain on the project, given that they have a lower status than those who perform repetitive and tedious work?

Easily-learned repetitive labour is nearly always paid less in real life than labour which requires either specialised learning, or some innate but scarce skill. The simple reason for this is supply and demand. Rare or difficult-to-acquire skills are by definition in short supply, and will attract a higher price than common, easily acquired skills (at least, to my simple mind - I don't know any economics).

So why is the situation apparently reversed on Wikipedia? The statistics suggest that the majority of administrators use these low-value skills like vandal reversion, template adding, linking to the Estonian Wikipedia etc. Yet their status on Wikipedia is high, whereas that of 'content contributors' is low.

This post has been edited by Peter Damian:

[radek]

My blog post for today http://ocham.blogspot.com/2011/10/repetiti...-wikipedia.html on whether there are statistically measurable properties that distinguish 'content contributors' from wiki-gnomes. Conclusion: the statistical difference is strongly indicative of a real difference, discussed in detail on the blog.

Remaining questions: why do content contributors remain on the project, given that they have a lower status than those who perform repetitive and tedious work?

Easily-learned repetitive labour is nearly always paid less in real life than labour which requires either specialised learning, or some innate but scarce skill. The simple reason for this is supply and demand. Rare or difficult-to-acquire skills are by definition in short supply, and will attract a higher price than common, easily acquired skills (at least, to my simple mind - I don't know any economics).

So why is the situation apparently reversed on Wikipedia? The statistics suggest that the majority of administrators use these low-value skills like vandal reversion, template adding, linking to the Estonian Wikipedia etc. Yet their status on Wikipedia is high, whereas that of 'content contributors' is low.

Oh yeah Peter, one thing. Your methodology will overestimate "content creation" by admins for ones who hang out mostly at AN/I and AE. More precisely, their high edits per page will come from them posting frequently to these drama boards, rather than working on articles.

There's probably some bias on the other end too. Someone like Piotrus has a edit per page number of 3.75, which is somewhere in the middle. But that's because the guy creates LOTS of pages and works a LOT on each of them. So there you'd have to control for total number of edits.

Actually, I think you could somehow use the Namespace Totals % which are given to separate out the repeated edits to actual articles vs. repeated edits to drama boards and user's talk pages. That would give a more accurate and relevant ratio for your purposes (I'd have to think for a few minutes how to do it which I might)

[Peter Damian]

Oh yeah Peter, one thing. Your methodology will overestimate "content creation" by admins for ones who hang out mostly at AN/I and AE. More precisely, their high edits per page will come from them posting frequently to these drama boards, rather than working on articles.

There's probably some bias on the other end too. Someone like Piotrus has a edit per page number of 3.75, which is somewhere in the middle. But that's because the guy creates LOTS of pages and works a LOT on each of them. So there you'd have to control for total number of edits.

Actually, I think you could somehow use the Namespace Totals % which are given to separate out the repeated edits to actual articles vs. repeated edits to drama boards and user's talk pages. That would give a more accurate and relevant ratio for your purposes (I'd have to think for a few minutes how to do it which I might)

Quite correct. That is evident from the pie chart - certain editors have a high 'blue' proportion, which is the WP: prefixed pages. There is no way round that except by selective querying of the database to get only article contributions.

And there are many other ways this figure is skewed. E.g. YellowMonkey has the highest number of FAs, yet a (relatively) low average e.p.p. of 3.69. All I can hope to give is a blunt figure that shows some correlation with our intuitive idea of 'content', namely something that cannot be produced by flitting from page to page, and which requires a long look at a single article, concerning the summary, the meaning of the parts.

Yes, you could use the % of namespace totals as a proxy, but I can think of several reasons why that might be skewed.

At the end of the day, I am trying to give one of many reasons why the concept of 'crowdsourcing' is badly flawed.

But that's because the guy creates LOTS of pages and works a LOT on each of them. So there you'd have to control for total number of edits.

I don't agree with that. If I create 100 pages and give 100 edits to each page, that's a very high e.p.p. of 100. Piotrus is probably contaminating his content work with mechanical repetitive editing. Which I understand well, because I relieve the writer's block doldrums with such activity myself.

Well, he can make whatever crappy analogies he wants to, but it still ain't. I think this just shows that Jimmy doesn't have much of a clue of what a market is or how it functions.

Well, he did publish a peer-reviewed paper on options pricing as part of his Ph.D., so he can't be a complete dunce. I think there are other explanations for why he said those things.

Ottava is not given to irony, but I assumed he was here.

I was being 100% honest.

OK so I was right about the bit before the 'but'.

[radek]

Quite correct. That is evident from the pie chart - certain editors have a high 'blue' proportion, which is the WP: prefixed pages. There is no way round that except by selective querying of the database to get only article contributions.

Well, there's no perfect way of doing it but you could just subtract off the blue to get a probably better estimate.
So edits per article page would be (1-(%wikipedia+%wikipedia talk))*average edits per page

Ideally you'd want to adjust the number of "pages" as well by subtracting AN/I and AE or whatever, but since there aren't that many of these pages it won't get too skewed.

The only possible exception is FAR pages which also count as "wikipedia" (blue) even though a lot of that is obviously content related.

The real difficulty is adjusting for # of edits on users' talk, since there's no way to tell how many different user talk pages a particular person posted to. And a lot of these admins basically spend the majority of their time politickin' on each others' talk pages so that's really something which should be taken into account. For example, Fetchcommons has 28.26% of his posts to user's talk. Sandstein has 24.71%. SarekOfVulcan has 24.09%, Jechochman (who has a pretty high average edits per page - but that's not cause he edits articles a lot) 28.93%, Georgewilliamherbert 34.69% BWilkins 39.26% etc.
For comparison, only 6.62% of my edits are to users talk.

So none of the above have anything to do with average edits per ARTICLE page. Again, the difficulty is in adjusting both the numerator and denominator here.

Still I think the formula above would give a somewhat better picture of actual edits per article page.

And there are many other ways this figure is skewed. E.g. YellowMonkey has the highest number of FAs, yet a (relatively) low average e.p.p. of 3.69. All I can hope to give is a blunt figure that shows some correlation with our intuitive idea of 'content', namely something that cannot be produced by flitting from page to page, and which requires a long look at a single article, concerning the summary, the meaning of the parts.

Yes, and some people will work on articles on their word processor or sandbox and then just post the ready thing. Others (like me) like to do it bit by bit. So the measure is obviously going to miss that.

Yes, you could use the % of namespace totals as a proxy, but I can think of several reasons why that might be skewed.

At the end of the day, I am trying to give one of many reasons why the concept of 'crowdsourcing' is badly flawed.

Well, any statistic summarizes information, almost by definition. And when you summarize information, by definition, you're going to loose some information (the only alternative is to somehow look at every single edit ever made at Wikipedia simultaneously). That doesn't mean that describing data with statistics is useless.

[EricBarbour]

For example, Fetchcommons has 28.26% of his posts to user's talk. Sandstein has 24.71%. SarekOfVulcan has 24.09%, Jechochman (who has a pretty high average edits per page - but that's not cause he edits articles a lot) 28.93%, Georgewilliamherbert 34.69% BWilkins 39.26% etc.

All of whom are notoriously contentious and abusive admins.
And none of whom adds very much in article content.

This chart is actually not bad, although there are some exceptions (but not very many).
Bear in mind that many of those "wiki gnomes" are heavy users of bots that scrape
from other websites. I would call them something more descriptive, like "Benders". (IMG:smilys0b23ax56/default/smile.gif)
(That's because Futurama is an extremely popular subject among WP admins....)
(IMG:http://upload.wikimedia.org/wikipedia/commons/5/59/DIV_LABOR_WIKI.png)

This post has been edited by EricBarbour: