From Jon Udell:
Abandoning taxonomy is the first ingredient of success. These systems just use bags of keywords that draw from - and extend - a flat namespace. In other words, you tag an item with a list of existing and/or new keywords. Of course, that idea's been around for decades, so what's special about Flickr and del.icio.us? Sometimes a difference in degree becomes a difference in kind. The degree to which these systems bind the assignment of tags to their use - in a tight feedback loop - is that kind of difference.
Feedback is immediate. As soon as you assign a tag to an item, you see the cluster of items carrying the same tag. If that's not what you expected, you're given incentive to change the tag or add another. If your items aren't confidential and online-only access is sufficient, this can be a great way to manage personal information. But the real power emerges when you expand the scope to include all items, from all users, that match your tag. Again, that view might not be what you expected. In that case, you can adapt to the group norm, keep your tag in a bid to influence the group norm, or both.
Jon's insight calls my attention to the fact that a good chunk of my meme tracker idea has already been implemented. De.licio.us is, in part, a meme tagger. If you added the Bayesian analysis to compare overlap in contents from items with the same tag and used the Google API to send search strings from the Bayesian corpus, you'd basically have it. You could add the spider that gathers the metadata necessary to track propagation later on, but the essentials for the purpose of aggregating examples of the meme are (a) tagging, (b) Bayesian analysis, and (c) search on the results of the analysis.
Thanks to D'Arcy Norman for pointing out Udell's article.