Hi Jeremy: This seems to be implied in your approach... but to reiterate: since the encyclopedia is a graph, it would be most useful to start by looking at centrality measures etc. there. If you define the "social" network (of people, where A<->B if they've edited the same page), then clearly the two graphs are "related". But what might you learn by comparing the two?
- You might find people who have contributed a lot to a lot of articles (but especially more central ones?) - You might find people who have contributed a lot to only (relatively) few articles (perhaps especially more fringe topics?) - You might find people who have contributed a little to a lot of articles (how does this relate to centrality?) - and of course you might find lots and lots of people who have contributed a little to just a few articles (how does this relate to centrality?) That would likely be good enough for a first paper... Thinking further, each of the cells in this little 2x2 grid is presumably an "attractor", so you don't necessarily expect to see people cross from one cell to another. But it could be interesting to for these crossings... and here, for a second research phase, you could try using the "social" data to see how particular things like conversations on talk pages or reverts can motivate or demotivate people... I think there's already a lot of work on this, but I'm not sure if it's backed up by the same sort of data intensive approach you seem to be proposing. Good luck, and I'll be interested to know more about your work and results as this develops. Joe On Wed, Sep 5, 2012 at 8:43 PM, Jeremy Foote <[email protected]> wrote: > I am a brand new Master's student at Purdue. For my Social Network Analysis > class, I'm thinking about doing a project about whether a Wikipedian's > centrality in a network can be used as a predictor of future participation. > I've spent the afternoon looking for relevant literature. I found the very > interesting > > "Validity Issues in the Use of Social Network Analysis with Digital Trace > Data" by Howison, Wiggins, and Crowston > and > "Network analysis of collaboration structure in Wikipedia" by Brandes et al. > > I'm wondering if there are other papers about how to translate Wikipedia > into a network structure, or even more specifically relating to node-level > centrality measures and participation measures. > > Very many thanks, > Jeremy Foote > > _______________________________________________ > Wiki-research-l mailing list > [email protected] > https://lists.wikimedia.org/mailman/listinfo/wiki-research-l > _______________________________________________ Wiki-research-l mailing list [email protected] https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
