info@infospaces.it
In recent times, an unprecedented amount of Web content has begun to be generated through web logs, wikis and other social tools thanks to lower technology and cost barriers. A new host of content creators is emerging, often individuals with the will to participate in discussions and share their ideas with like-minded people. This is to say that this increasing amount of varied, valuable content is generated by non-trained, non-expert information professionals: they are at the same time users and producers of information.
We have gone past a critical mass of connectivity between people that has introduced a new revolutionary ability to communicate, collaborate and share goods online.
To respond to these increased informational and exchange needs, new communication models are emerging and producing an incredible amount of distributed information that information management professionals, information architects, librarians and knowledge workers at large need to link, aggregate and organize in order to extract knowledge.
The issue is whether the traditional organizational schemes used so far are suitable to address the classification needs of fast-proliferating, new information sources or if, to achieve this goal, better aggregation and concept matching tools are required.
Folksonomies attempt to provide a solution to this issue, by introducing an innovative distributed approach based on social classification.
For centuries, classification has been used to provide context and direction in any aspect of human knowledge. Our mind seems to define, understand and describe the external world by tracing boundaries and fitting things into classes, containers with a name. As human beings, we need to clearly know our relative position and the viable routes towards other places. In a physical world, we design and use maps, coordinates, graphs, diagrams, signposts. Equivalent tools are needed to find our way in the virtual world.
Much work has been done by librarians and information scientists to create appropriate and powerful classification systems. Classification requires the design and consistent use of a scheme for a systematic organization of knowledge. See [1].
Traditionally, there are two different approaches to classification:
Hierarchical - enumerative: a taxonomic top-down scheme, in which knowledge is divided into progressively narrower and more specific categories (a hierarchy). Enumerative classification assigns names to every subject and enumerates them, typically in a systematic order. When this approach is applied to libraries, where
physical objects – books – are classified, each object is located in a single place, often with one only path to get there. See [2].
Analytical - synthetical: a faceted bottom-up scheme that breaks down a subject into individual concepts (analytical) and provides rules to use these concepts in constructing headings for composite complex subjects (synthetical). New elements can be developed as new concepts emerge, often without superseding the previous categorization activity.
Hierarchical - enumerative schemes are basically trees of containers connected by parent-child relationships and with one only path from the “root” to the “leaves”. We are very familiar with this kind of knowledge organization which, anyway, has a number of drawbacks:
Unlike the above, Analytical - Synthetical schemes give up enumerating classes by describing items through a combination of aspects (facets). In a faceted classification scheme, the facets may be considered to be dimensions in a Cartesian n-dimensional space, and the value of a facet is the position of the object in that dimension. Instead of imposing a pre-determined hierarchy, items can be placed on-the-fly, by evaluating their inherent characteristics, and can be retrieved by users using the same item properties, either one at a time or all together.
Faceted classification can be applied to large homogeneous datasets and suggests an explorative approach, whereby a large dataset is progressively filtered through the user's choices. Users can restrict the resulting dataset at each step, until they arrive at a group of items that meets their needs. See [2].
In this flexible and scalable approach, an item can be associated to, or better described, by more than one facet, and new facets can be quite painlessly and freely introduced to express new concepts.
Ten years after the first homepages, today’s mass phenomenon is weblogs, online diaries or journals that either individuals or groups publish and share with others on the Web. We now have hundreds of thousands active weblogs, most of them powered by simple content management systems. Thousands of weblogs are created and die everyday, in every country of the world. Weblog authors, or bloggers, are entering the realm of politics and large corporations at an incredibly fast pace, linking, posting, trackbacking and commenting in an enormous living network. Now, everyone can have their own blog to express opinions, create communities, collect links and keep an online diary.
The Web publishing process has come to the masses thanks to lower technology and cost barriers.
Blogging and content management software provides every one interested with extremely simple and accessible tools to update a website every day, almost effortlessly and at no cost. See [3].
Blogging is just one component of the emerging, more general concept of social software, a technology "which supports, extends, or derives added value from human social behavior – message-boards, musical taste-sharing, photo-sharing, instant messaging, mailing lists, social networking". See [4].
The point here is that we have gone past a critical mass of connectivity between people that introduced a new revolutionary ability to communicate, collaborate and share goods online.
Beside blogs and wikis, other tools of social connection are emerging, such as photo sharing, social bookmarking, to-do-list sharing.
These tools are producing an incredible amount of distributed information that we need to link, aggregate, organize in order to extract knowledge. To achieve this goal, better aggregation and concept matching tools are required.
From what we saw in the previous paragraphs, traditional schemes of classification work better when a domain presents these properties:
In other words, to classify cleanly, formal categories should be identified that do not change over time, contain homogeneous entities and are capable of describing all the items in a corpus. DDC (Dewey Decimal Classification) is an example of traditional classification scheme often applied in libraries. Libraries appear to be homogeneous sets of items (books), that can be grouped in hierarchical, formal, pre-defined classes and in which new items are added at a reasonable pace.
Another fundamental point to take into account is the target audience of the classification strategy. Taxonomies and controlled vocabularies work by establishing a clear view and organization of the corpus on which users have to agree in order to use the classification scheme properly.
Traditional classification schemes require also:
Expert cataloguers
Authoritative source
Expert users
Using a sound and complete classification scheme requires professionals to do the job, a common clear view of the domain and skilled users that understand the categories and the structure of the classification to use it without problems. See [5].
On the other hand, sprawling, heterogeneous information sources make up an enormous, ever-changing, time-sensitive, not-clearly defined corpus of items to classify, without a central authority, targeted at a heterogeneous and increasing group of users. This situation requires new and different classification strategies.
The Web today fits neatly in this description. On the Web, the direction is scalability, flexibility, fluidity and simplicity to satisfy the demanding needs of millions of people with different cultural and social backgrounds all over the world. Under these circumstances, traditional precise classification schemes become expensive (to create and maintain) and probably lose the capability to match the user’s way of thinking and organizing the world.
Folksonomies provide an approach to address Web-specific classification issues.
A folksonomy is a user-generated classification, emerging through bottom-up consensus (see [6]). A fusion of the words folks and taxonomy, the first use of the term folksonomy has been attributed to Thomas Vander Wal. Taxonomy comes from "taxis" and "nomos" (from Greek). Taxis means classification. Nomos (or nomia) means management. Folk is people.
The term was coined in the AIfIA mailing list to mean the wide-spreading practice of collaborative categorization using freely chosen keywords by a group of people cooperating spontaneously. See [7].
Folksonomies are not a theory or a top-down strategy: they were born out of a feature (folk classification tools) introduced by software like Del.icio.us (http://del.icio.us), Flickr (http://www.flickr.com), 43things (http://www.43things.com), Furl (http://www.furl.net), Technorati (http://www.technorati.com), etc. and from people using these platforms to tag their contents (links, photos, etc).
Folksonomies require people to associate keywords with content. Using popular keywords gives them the reward of visibility, to see one’s own content gravitate in evidence in the system (for example on the homepage).
In a bottom-up distributed and collaborative grassroots approach, tagging or folksonomy is a manifestation of people moving away from hierarchical authoritative schemes. Rather than learning yet another imposed external scheme to classify items and to restrict, to some extent, the user’s thinking, people started to associate their own tags to the items they wanted to collect and share. In a social distributed environment, sharing one’s own tags makes for innovative ways to map meaning and let relationships naturally emerge. See [8].
Folksonomies are not simply visitors tagging something for personal use: they also are an aggregation of the information that visitors provide. The power of folksonomy is connected to the act of aggregating, not simply to the creation of tags. Without a social distributed environment that suggests aggregation, tags are just flat keywords, only meaningful for the user that has chosen them. The power is people here. The term-significance relationship emerges by means of an implicit contract between the users.
The concept on which folksonomies are based can be applied to everything that we can aggregate. The key point is in having an activity to observe that:
Is explicit
Can be aggregated
Produces benefits to users (this is the reason for adding tags)
Is relevant to the purpose of a site.
Though working on a different mechanism, an example of aggregation based on user activity and interest is the recommendations feature on Amazon.com: the aggregated activity here, instead of tagging, is users reading a product page. This activity is explicit, can be aggregated, is meaningful for users and, by transparently tracing user behavior, produces useful insights for the company. See [9].
Two of the best known examples of social software using folksonomies are probably Flickr and Del.icio.us. They are aimed at different user needs and profiles, but the basic idea is simply to make people share items annotated with tags.
Flickr is a social photo management and sharing tool that allows users to easily
upload and share digital photos.
Del.icio.us is a social bookmarks manager. It allows its users to easily add web pages to personal collections, to tag them, and to share their collections with others.
As Jon Udell defined them on a more formal level, both Del.icio.us and Flickr are collaborative systems for:
building a shared database of items,
developing a flat metadata vocabulary,
performing metadata-driven queries (also using multiple tags at a time),
monitoring change in areas of interest,
discovering the most popular metadata.
We have always believed that nobody (except for professional indexers) would have assigned metadata or classified content, and that even if someone wanted to try, they would have produced useless inconsistent taxonomies. The main reasons for this were the lack of benefits for the user in classifying things and the complexity of the operation. Starting from this belief, nobody could have imagined that users of Flickr and Del.icio.us would assign tags to content everyday and that these tags could be the gateway to a new experience of the Web, opening fascinating and innovative possibilities of navigation and search.
Put simply, this is how this software works: users tag an item with a list of existing and/or new keywords they identify at the moment or others have already provided. Keywords are for sure not new on the Web, but these tools add some new relevant properties:
Feedback is immediate. Starting from content of their interest and assigning one or more tags, users are categorizing it for later retrieval.
Serendipity. Starting from a tag (proposed by the user or others) it is possible to discover all items, from all users, that match that same tag simply with a click.
Other powerful features: the user experience is deeply enriched by many innovative tools for browsing and better organizing the tag space. A tag cloud is shown in which popular tags are presented, thus giving evidence of their frequency of use. It is possible to automatically manage tags by renaming them or adding more tags to content. Tags can be used to perform data queries in clever ways, for example by combining tags. By recording user behavior, tags can be correlated and queries can be expanded following the system tips so as to discover other useful items. See [10].
Flickr, Del.icio.us and other social tools that leverage the power of folksonomies aim at different user profiles and show several trends of use. In other words, the nature of the folksonomies they produce is quite different.
As explained by Thomas Vander Wal (see [11]), we can distinguish two typologies of folksonomy, each associated with specific properties and suggested use:
Broad Folksonomies
Narrow Folksonomies
A broad folksonomy (as the one of Del.icio.us) is the result of many people tagging the same item. Every user can tag the object in a different way following their own mental model, vocabulary and language. This approach tends to show a power law curve and a long tail effect1.
In a broad folksonomy, the power law reveals that many people agree on using a few popular tags but also that smaller groups often prefer less known terms to describe their items of interest.
Therefore, a broad folksonomy provides a tool to investigate trends in large groups of people describing a corpus of items and can be used to select preferred terms or extract a controlled vocabulary.
The real power of broad folksonomies is in the richness of the mass, in people explicitly exposing their way to define and describe things that leads to the long tail and power curve. These effects are simply absent in personomies, i.e individuals tagging their own self-produced or uploaded content.
A narrow folksonomy (as the one of Flickr), on the other hand, is the result of a smaller number of individuals tagging (using one or more tags) items for later personal retrieval or for their own convenience.
Narrow folksonomies lose the richness of the mass, but provide benefits in tagging objects that are not easily findable with traditional tools (full-text search or other text-related tools) or that cannot be simply described in current text-based software on the Web.
A narrow folksonomy provides various target audiences (maybe with a rather specific shared vocabulary) with the instrument to add tags in their own language. This property makes later retrieval fast, efficient and enjoyable.
Much debate is currently going on about folksonomies. From this discussion, a number of properties have emerged.
Detractors of Folksonomies highlight the following drawbacks:
Folksonomies imply a lack of precision for the variability of language, as a function of user behavior and the lack of synonym control in current implementations. However, the latest software releases have often a correlation feature that, given a tag, shows related tags, i.e tags that people have used in conjunction with the given tag to describe the same item. Moreover, the trade-off between simplicity and precision makes sense in most practical cases.
Proposed tags have no hierarchy. Folksonomies are a flat space of keywords and it is hard to think of real people crafting complex structures of tags to describe their objects (posts, photos, etc) or objects from other sites.
Folksonomies have a very low findability quotient. They are great for serendipity and browsing but not aimed at a targeted approach or search. See [12,13].
Tags do not scale well if you are looking for specific targeted items, but that is not their purpose.
On a positive note, supporters of folksonomies underline that:
Not all the limitations of folksonomies are defects. Better, they can be seen as features and design choices. “There is a loss in folksonomies, of course, but also gain, so the question is one of relative value”. See [14].
Since the organizers of information in blogs and social software tools are usually the primary users, folksonomy produces results that more accurately reflect the population’s conceptual model of the information. Folksonomies are simple, emergent and iterative systems. Their advantage over traditional top-down classification is their capability of matching users’ real needs and language, not their precision.
An interesting property of folksonomies is that they are inclusive. They include everyone’s words and vocabulary without leaving anything out. There is no central authority imposing a top-down view, and every voice gains its space. This aspect and the power law trend imply that by using folksonomies, we can also discover long tail topics: original, non-mainstream ideas can emerge from the interest of a small fraction of the population to the attention of the mass. See [15].
The long tail paradigm is also about discovery of information, not just about finding it. In a word: serendipity. Controlled vocabularies, on the other hand, are mostly about finding information. As the amount of information increases, making anything simply findable could become impossible or economically not viable. In other words, maintaining a top-down taxonomy is a hard task. On the other hand, a folksonomy, though naturally less precise, invites users to investigate, to surf, to discover the site content in an enjoyable way. According to Donna Maurer, to discover is: “to notice or learn, especially by making an effort”. This definition stresses the learning aspect, rather than the locating aspect. Folksonomies imply the task of retrieving information in a broader context where the search process is broken down into many smaller ‘finding’ tasks in an organic enriching experience. See [16].
Folksonomies are a forced move. While some distinguished information architects are still skeptical about social tagging, there are good reasons to anticipate broad adoption of this approach. The reason is not that folksonomies are better than controlled vocabularies or expert judgment. Well-designed metadata is better than folksonomies on traditional axes of comparison. However, the environment makes the difference: it does not matter whether we “accept” folksonomies, because we are not going to be given that choice. The mass amateurization of Web publishing makes the mass amateurization of cataloguing a forced move. Folksonomies are a trade-off between traditional structured centralized classification and no classification or metadata at all. And they are the best we actually have. See [17].
Controlled vocabularies are not practically and economically extensible to the majority of cases where tagging could be used. Building, maintaining, and enforcing a sound controlled vocabulary is often simply too expensive in terms of development time and of the steep learning curve needed by the user of the system to learn the classification scheme. In other words, folksonomies are better than nothing, when traditional classification is not viable. See [18].
According to Jess McMullin (see [19]), social tagging can be considered “a low-investment bridge between personal classification and shared classification”. As a matter of fact, also faceted classification offers more scalability, flexibility and a semantic approach to classification. However, facets could not be the right answer if people have to classify the content they produce as it happens today. When the “number of terms and their combinations are expanded, faceted classifications multiply the number of decisions required to classify a given document” adding a significant cognitive cost to classification. Often, this cognitive investment is too high for the common bloggers that simply prefer describing their posts with free keywords.
In brief, using the words of Timo Hannay (see [20]), a folksonomy is “liberating, not restrictive; bottom-up, not imposed; relational, not hierarchical. It also cleverly harnesses selfish acts and directs them towards the common good. But most of all, it just seems to fit the way our brains work”.
Folksonomies are not limited to the geek world or to the blogosphere. Enterprises have also started blogging and experimenting with folksonomies. An example is IBM’s Intranet that serves 315,000 IBM employees worldwide in different languages and with multiple roles and information needs. While actually using a controlled taxonomy, they have announced to start experimenting with folksonomy to keep information updated and organized following their users’ personal way of accessing the system. See [21].
In the direction of facing the intrinsic precision loss of folksonomies, Jess McMullin proposes to complement social classification with other classification approaches: “automated keyword extraction, tag suggestions built into the tagging tool as the tag is typed [see Google Suggest and Ajax technology], mapping ad-hoc tags to structured facets, and top-down classification oversight by information professionals”. See [19].
Large corporations are often made of independent silos unable to communicate with each other and not sharing a common vocabulary. The same thing can have different names in different silos. A typical argument against the introduction of folksonomies in a corporate environment is that their use as a basis for retrieving documents from corporate archives would still require a common language, a shared vocabulary, spoken by the entire company, allowing the use of a well-defined label or set of labels for every article. This is not true: while the vocabulary is not the same, people are classifying the same real things underlying the terms used to name them. This knowledge allows the creation of a mapped folksonomy between the language of individuals and the corporate language as a sort of synonym ring. Every user will retrieve documents using the terms of their specific vocabulary that the system would match to the corporate vocabulary. See [22].
Leaving aside classification as a goal in itself for a moment, folksonomies appear as a means of self-expression in a group and, in a more general context, it can suggest useful possibilities of aggregation and analysis. The aggregation of tags that people assign to items is revealing of their personal ways to express concepts and the means by which they communicate in their group.
This analysis of people behavior and perceptions can be accelerated by sharing folksonomies. A new XHTML microformat has been proposed for this purpose by Bud Gibson and it is named xFolk. See [23].
As a side benefit, tagging enhances the creation of communities around classification. People using the same keywords have a common interest. Therefore, folksonomy can be a “ridiculously low-cost kind of community that’s nothing more than a beneficial side effect of people tagging documents for their own future recall” as Gene Smith writes in his post after IA Summit 2005. See [24].
Folksonomies are not the solution to every modern problem of classification and they are not alternative to the traditional classification schemes librarians have designed over the years. They are more simply a powerful and innovative tool that should be applied only under the right circumstances and considering their own specific properties and the differences in respect to other classification schemes as taxonomies and faceted classification.
Here are outlined some of the major differences between folksonomies and traditional classification:
Folksonomies are an emergent flat set of tags without a structured hierarchical organization and created from the users in the same moment in which they publish, insert or catalogue items.
Taxonomies and faceted systems are typically designed before starting to catalogue items and are organically crafted by professionals trying to guess user needs and content typologies.
Taxonomies and faceted systems propose an authoritative centralized view, while folksonomies leave a decentralized collaborative view to emerge.
Taxonomies and faceted systems have a high precision, are aimed at avoiding ambiguity, and their hierarchical structure contributes to give context to terms. Tagging systems lack precision by definition and currently do not provide synonym control.
Using a sentence from David Weinberger, “Trees are neat; piles of leaves are messy”.
Because of these differences, taxonomies, facets and folksonomies have different potential areas of application:
Taxonomies are suitable for classifying corpora of homogeneous, stable, restricted entities with a central authority and expert or trained users, but are also expensive to build and maintain.
Faceted systems (a sort of polyhierarchy) are useful with a wide range of users with different mental models and vocabularies. They are also more scalable because new items (for users) and new concepts (for cataloguers) can be added with a limited impact and with no need to start a new classification from scratch.
Folksonomies require people to do the work by themselves for personal or social reasons. They are flat and ambiguous and cannot support a targeted search approach. However, they are also inexpensive, scalable and near to the language and mental model of users.
For more information see [25].
Folksonomies are a new, rapidly evolving approach to classification of digital objects. Much has still to be discovered and tested. What we have not created yet is probably “a middle ground, somewhere between the pure democracy of bottom-up tagging and the empirical determinism of top-down controlled vocabularies”. In this scenario, “users could freely create, adopt or reject terms stored in a distributed repository that gets administered by a representative authority that ‘owns’ the vocabulary”. See [6,26].
All that we have to do is to merge and leverage emerging and traditional tools to improve findability. Somewhere at the intersection of those two models is a more powerful framework for identifying, sharing, and finding information.
The goal is a metadata ecology, where the best tools we have bend towards a real user-centred design. See [13].
The increasing interest in folksonomies is confirmed by new projects like Freetag. Freetag is an API written in PHP for setting up a folksonomy on a website. With such tools, in a near future, we should be able to leverage the power of folksonomies outside of the original environment that introduced them, such as Flickr. See [27].
Traditional hierarchies for organizing information (or reality) will not be replaced by tags, but through tagging we are finding new ways of thinking about classification and new applications for organizing and sharing knowledge. See [28].
This paper has been written with the help of some clever and supportive friends.
First of all, I want to thank Antonella Pastore (information architect currently working on user research, strategic consulting and evaluation of information systems for international organizations) for the invaluable editorial and linguistic help and for the fundamental advice on some central parts of this paper.
Another thankful mention goes to Claudio Gnoli (researcher, teacher and president of the Italian chapter of the International Society for Knowledge Organization) for the inspiration and the enlightening explanations.
A special thought goes to Peter Van Dijck and Luca Rosati for the encouragement and the discussions about all things information architecture.
Moreover, I would like to thank James Weinheimer (information management specialist at the FAO of the UN, and moderator of the ASIS&T SIGIA mailing list) for the kind and insightful review.
Finally, thanks to everyone who kept on reading until the end of this article.
Content Classification - http://encyclozine.com/Reference/Library/Classification/
Innovation in Classification – September 23, 2001 - Peter Merholz - http://www.peterme.com/archives/00000063.html
(Weblogs and) The Mass Amateurisation of (Nearly) Everything... – September 03, 2003 - Tom Coates -http://www.plasticbag.org/archives/2003/09/weblogs_and_the_mass_amateurisation_of_nearly_everything.shtml
An addendum to a definition of Social Software - January 5, 2005 – Tom Coates -http://www.plasticbag.org/archives/2005/01/an_addendum_to_a_definition_of_social_software.shtml
Ontology is Overrated: Categories, Links, Tags - Clay Shirky - http://shirky.com/writings/ontology_overrated.html
Folksonomy - August 23, 2004
- Alex Wright - http://www.agwright.com/blog/archives/000900.html
Folksonomy - Wikipedia - http://en.wikipedia.org/wiki/Folksonomy
Introduction: Jon Lebkowsky - May 3, 2005 - Jon Lebkowsky - http://tagsonomy.com/index.php/introduction-jon-lebkowsky/
I’ve Heard of Folksonomies. Now How do I Apply them to My Site? - February 01, 2005 - Joshua Porter - http://www.bokardo.com/archives/applying_folksonomies/
Collaborative knowledge gardening - August 20, 2004 - Jon Udell - http://www.infoworld.com/article/04/08/20/34OPstrategic_1.html
Explaining and Showing Broad and Narrow Folksonomies - Thomas Vander Wal - February 21, 2005 - http://www.personalinfocloud.com/2005/02/explaining_and_.html
Ethnoclassification and vernacular vocabularies - August 30, 2004 - Peter Merholz - http://www.peterme.com/archives/000387.html
Folksonomies? How about Metadata Ecologies? - January 06, 2005 – Louis Rosenfeld - http://louisrosenfeld.com/home/bloug_archive/000330.html
Folksonomy - August 25, 2004 - Clay Shirky - http://www.corante.com/many/archives/2004/08/25/folksonomy.php
Controlled Vocabularies Cut Off the Long Tail - March 09, 2005 - Joshua Porter -http://bokardo.com/archives/controlled_vocabularies_long_tail/
Findability vs discoverability – March 08, 2005 - Donna Maurer -http://www.maadmob.net/donna/blog/archives/000609.html
Folksonomies are a forced move: A response to Liz - January 22, 2005 - Clay Shirky - http://www.corante.com/many/archives/2005/01/22/folksonomies_are_a_forced_move_a_response_to_liz.php
Folksonomies + controlled vocabularies - January 07, 2005 - Clay Shirky - http://www.corante.com/many/archives/2005/01/07/folksonomies_controlled_vocabularies.php
The Cognitive Cost of Classification - August 19, 2004- Jess McMullin - http://www.interactionary.com/index.php?cat=7
Introduction: Tino Hannay - May 02, 2005 -Timo Hannay - http://tagsonomy.com/index.php/introduction-timo-hannay/
IBM’s Intranet and Folksonomy - March 6, 2005 - Bud Gibson- http://thecommunityengine.com/home/archives/2005/03/ibms_intranet_a.html
Using mapped folksonomy to break corporate silos - February 16, 2005- Bud Gibson- http://thecommunityengine.com/home/archives/2005/02/using_mapped_fo.html
Folksonomy — Practical Application and xFolk - Bud Gibson -March 29, 2005 - http://thecommunityengine.com/home/archives/2005/03/folksonomy_prac.html
IA Summit Folksonomies Panel – March 08, 2005 – Gene Smith - http://atomiq.org/archives/2005/03/ia_summit_folksonomies_panel.html
Taxonomies and Tags: From Trees to Piles of Leaves - David Weinberger - - http://www.hyperorg.com/blogger/misc/taxonomies_and_tags.html
Bridging the Gap: Folksonomy and Taxonomy - February 11, 2005 - James Melzer- http://www.jamesmelzer.com/bearings/archives/2005/02/bridging_the_ga.html#more
Freetag - an Open Source Tagging / Folksonomy module for PHP/MySQL applications - http://getluky.net/freetag/
Introduction: Jon Lebkowsky - May 3, 2005 - Jon Lebkowsky - http://tagsonomy.com/index.php/introduction-jon-lebkowsky/
Faceted Classification of Information - The Knowledge Management Connection - http://kmconnection.com/DOC100100.htm
Metacrap: Putting the torch to seven straw-men of the meta-utopia - August 26, 2001 - Cory Doctorow - http://www.well.com/~doctorow/metacrap.htm
Social Bookmarking Tools - April 2005 - T. Hammond, T. Hannay, B. Lund, and J. Scott http://www.dlib.org/dlib/april05/hammond/04hammond.html
Folksonomies - Cooperative Classification and Communication Through Shared Metadata – December 2004 - Adam Mathes - http://www.adammathes.com/academic/computer-mediated-communication/folksonomies.html
Bookmark, Classify and Share: A mini-ethnography of social practices in a distributed classification community - http://ideant.typepad.com/ideant/2004/12/a_delicious_stu.html
1 In nature, events deviating from the average are rare. They follow a bell curve, a curve with a marked peak (a Gaussian curve). Power law distributions are very different from Gaussian curves: they do not have a peak, a characteristic value, but they look like continuously decreasing curves in which a large amount of tiny events (the long tail) coexist with a few anomalously very large ones. See “long tail” on wikipedia