I'm just going to talk about tagging and folksonomies for a bit. Tagging and folksonomy is part of an overarching 'goal' to create accurate metadata by brute force. Think of it as a neural network of information categorization. We all interpret information differently; while one person may tag a website or page as 'technology' another person may tag it as 'pseudo-science' depending on their point of view. The theory goes, reality as determined by the massive public will create order from chaos and correct categories by popular choice. I think the fallacies in such an idea are fairly self-evident but it certainly does a better job of ordering information than manually doing it.
How tagging, folksonomy, and metadata works is this: Say I show 10,000 people a picture of a flower and ask them to 'tag' it, with as many tags as they want. Chances are it's going to end up with 9,900 tags of 'flower', and if the flower is red, then probably 4,000 tags of the word 'red'; if it's a rose, you'd get tags of 'rose' and for the horticulturalists out there who know it's exact species name. Some nerdy horticulturalist might even tag it the full series: Plantae Magnolioptea Magnoliopseta Rosales Rosaceae Rosoideae Rosa. What you end up with is a array of tags with the most popular one (flower, rose) with less popular ones (beautiful, Rosoideae). This creates metadata, which allows search programs to find what you're looking for more accurately than by just showing you all images of flowers. If you for example searched for 'beautiful red roses', the search engine could search for the most significantly tagged photos with the tags 'beautiful, red, and roses' first. Without this, searches would have no choice but to simply display all pictures with those descriptions in an arbitrary non-organic list order.
In a strange way, tagging and folksonomy has some similarities to how we as humans learn. People learn through repetition of information. People for example can identify the sound of a keyboard going click-clack because they've heard it so many times. And then they know it's probably connected to a computer; and that a person is probably writing something on a computer. We connect this sound with tags like 'keyboard', 'computer', and 'writing' with less popular tags like 'paper', 'exam', and 'microsoft word'. By these personal tags, we might make an assumption just by hearing the sound that 'Someone is typing on a keyboard connected to a computer and they might be writing a paper on microsoft word'. Just like in the webworld, less popular metatags are more subjective, less accurate, and therefore less important.
In a weird way, this is how the internet and information is learning about us.
ZF