SBS are relatively new and have sparked much conversation among bloggers, a few mentions in the popular press, as well as a academic papers. Most of these efforts attempt to define what SBSs are and note their strengths and weaknesses. Some advocate for particular definitions and attempt to shape the still nascent development of SBS.

SBS are partially built on the familiar model of implicit metadata discovery most popularly employed by Google.

PageRank relies on the uniquely democratic nature of the web by using its vast link structure as an indicator of an individual page's value. In essence, Google interprets a link from page A to page B as a vote, by page A, for page B. But, Google looks at more than the sheer volume of votes, or links a page receives; it also analyzes the page that casts the vote. Votes cast by pages that are themselves "important" weigh more heavily and help to make other pages "important." ("Our search: Google technology", 2005)

Other familiar uses of implicit metadata include academic citation analysis, and Technorati's Cosmos feature for ranking bloggers (see http://www.technorati.com). Each link on delicious has a popularity rank, showing how many other users have bookmarked it, and there is an option to see items ranked by popularity within a tag or system wide (see http://del.icio.us/popular and http://del.icio.us/popular/folksonomy). The tags in the delicious system are explicit categorizations by users, and the resulting popular and tag pages are compiled from individual user accounts. User collectivity, i.e. the level explicit intention to classify the links for others, varies.

The ability for the collective database to be used entirely for individual ends makes delicious and other SBS unique among shared databases. They conquered the communication dilemma that pits "the interests of the collective against the self-centered interest of individual members" (Kalman et al., 2002; Yuan et al., 2005). But through solving this dilemma it has brought new concerns to the fore.

... the code of SBSs removes [sic] the need for humans to negotiate meaning around classification. This can be liberating as well as alienating. Liberating because, as I suggested above, there is no governing body dictating what the classification scheme should be. Alienating because, without the mechanisms for deliberation, meaning becomes atomistic, a reflection of what the software has parsed and aggregated from detached individuals, not what has emerged through consensus and deliberation. (Mejias, 2005)

One scholar of classification and library science, Star, advocates that "information systems should not be designed simply to represent consensus but to accommodate the dissent that can be expected to appear among the various communities participating in their use." (Albrechtsen, 1998). Delicious does that, but through removing human negotiation.

SBS are not the first effort to topple top-down taxonomies. "Social critics of classification systems argue that the choice of categories reflects political choice and the often silent wielding of bureaucratic exercises of power" (Star, 1998). Star goes on to state "The enemy [of faceted classification]... is reified rigid attempts at universal descriptions of knowledge that are not grounded in people's needs or experiences."

The problem is akin to a situation in cultural anthropology where the people who were formerly "the natives" often prefer to describe themselves, and some reject expert descriptions, even the most sensitive and thoughtful ones. It seems that web naives would like the option to describe it for themselves, thank you very much librarians and cataloguers. This folk classification opens up interesting possibilities for analysis. At this point it is generally a worldwide technology elite that dominates delicious and other SBS, but as the population grows so do the sociological possibilities of analyzing tags, which are "the consensus already established around the use of certain words" (Mejias, 2005). As the data in SBS continues to expand, it can be put to use for good or ill.

The way a person or group of people classifies the things in the world has a tremendous impact on what they are able to know and how they are able to think. The most fundamental divisions of thinking are largely invisible until one comes in contact with other systems. This is contact happened when Foucault read a passage describing a Chinese encyclopedia in which it is written:

"animals are divided into: (a) belonging to the Emperor, (b) embalmed, (c) tame, (d) sucking pigs, (e) sirens, (f) fabulous, (g) stray dogs, (h) included in the present classification, (i) frenzied, (j) innumerable, (k) drawn with a very fine camelhair brush, (l) et cetera, (m) having just broken the water pitcher, (n) that from a long way off look like flies" (Foucault, 1994, pp xv).

Foucault goes on to say that the passage demonstrates the limitations of thought, because the seeming absurdity of these categories comes from the fact that it would be impossible for a Western mind to create them.
Another initially unfamiliar classification scheme is the tag cloud (see http://del.icio.us/tag/). Tag clouds are sets of tags often in alphabetical order and visually weighted by font size in proportion to popularity. Although a tag cloud is technically ordered by the alphabet and popularity it is unordered conceptually.

Further study is needed in order to characterize the type of social phenomena currently taking place on SBSs. I chose to study delicious because it is the first and most popular among them. In my pilot study I looked at feedback as an independent variable causing an increase in system use. I was only able to find one study that directly dealt with these variables. The study had an experimental design where feedback was varied. When the groups were able to see the contributions of other members a phenomena called social matching occurred where participants used the feedback to adjust their level of participation to match the group (Roy et al., 1996). This lead to my pilot hypothesis below.

Pilot Hypothesis: The amount of feedback the user receives (via browsing, web syndication, and third party applications) via the delicious system will positively influence how much the individual uses the system.

Below I will describe the method and results of testing the pilot hypothesis, but I now believe that there are more sophisticated and appropriate research questions that I will deal with in my master's thesis.