Folksonomy: Creating Metadata through Collaborative Tagging

Folksonomy: Creating Metadata through Collaborative Tagging

Stefan Bitzer (Georg-August-Universität Göttingen, Germany), Lars Thoroe (Georg-August-Universität Göttingen, Germany) and Matthias Schumann (Georg-August-Universität Göttingen, Germany)
DOI: 10.4018/978-1-60566-368-5.ch014
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Modern Web 2.0 technologies facilitate the collaboration and sharing of information among users, thereby enabling cooperative processes of information search. One kind of user participation is collaborative tagging, where individuals assign keywords to resources and objects on the Internet. Through the allocation of keywords, objects are enhanced with user-created metadata which results in the so-called folksonomies. This chapter focuses on the classification of tags based on function and user motivation, examines advantages and disadvantages of folksonomies, and provides a review of current applications using collaborative tagging. Future trends and potential developments are identified as they relate to the implementation of collaborative tagging in corporate settings.
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Folksonomies and Tagging

Vander Wal (2005) defines folksonomy as the outcome of individual free tagging of online content and resources in a social environment for one’s own retrieval. With this term, Vander Wal refers to the result of a process of collaboratively assigning keywords to resources or items on the Internet, the so-called collaborative tagging. Therefore, folksonomy is often used synonymously with the terms social classification, social indexing, or social tagging (Voß, 2007). Folksonomy is a portmanteau of the words folk and taxonomy (Bateman, Brooks, & McCalla, 2006). The naming, however, is disputed. Some see it as a misnomer because of the reference to taxonomy. A classification scheme like taxonomy is strictly hierarchic and contains relations, unlike a folksonomy, which consists of a flat namespace (Mathes, 2004). The vocabulary is not preassigned, instead the users describe the information and items within their own comprehension. The purpose of folksonomies is not categorization but connecting items and expressing their meaning through personal understanding (Vander Wal, 2005).

In the context of folksonomies, three elements have to be considered (Marlow, Naaman, Boyd, & Davis, 2006), namely, resources, tags used for describing the resources, and users who assign the tags. In broad folksonomies (as in Figure 1), many users describe the same item with a term from their personal vocabulary. Hence, similar or different tags can be assigned to an object (from 1 to 5). On the basis of all assigned tags, users are able to retrieve the described object. A common example of an application of broad folksonomies is a popular social bookmarking service, Del.icio.us1 (Lux, Granitzer, & Kern, 2007).

Figure 1.

Broad and narrow folksonomies

By contrast, in narrow folksonomies (Figure 1) there are only a few tags, mostly provided by the content creator and a group of a few people. Due to this, the number of tags and tagging persons is significantly lower than in broad folksonomies. Every tag is generally created and recorded once only, either by the content creator or a small group of selected users. Only new tags can be attributed to an object, which inhibits the possibility of counting tag frequencies. Accordingly, all tags are ranked equally and a tag distribution cannot be created. However, it can be shown via which tag users found the resource. The approach of the narrow folksonomy resembles professional indexing with controlled terms for thesauri or ontologies; in contrast, folksonomies have uncontrolled terms. Popular examples for narrow folksonomies (Cattuto, Loreto, & Pietronero, 2007) include services such as Flickr2 (photographs) or Technorati3 (blog posts).

Today folksonomies are implemented in various fields. In addition to a high diffusion of Web 2.0-based services, folksonomies are employed in corporate applications (Fichter, 2006). Capabilities have been found in indexing corporate blogs, podcasts and vodcasts (Peters, 2006); corporate social bookmarking (Damianos, Griffith, & Cuomo, 2006; Millen, Feinberg, & Kerr, 2006); and message boards (Murison, 2005). Furthermore, the use of folksonomies in public facilities has also gained popularity, for example, in art museums (Trant & Wyman, 2006) or public library catalogs (Spiteri, 2006).

Key Terms in this Chapter

Thesauri: Originating in bibliography, thesauri are taxonomies enhanced with primitive definite relations such as synonyms.

Tag Cloud: Weighted list with a visual description of user-generated tags. In tag clouds, tags are typically listed alphabetically, while the tag frequency is shown with font size or color.

Taxonomy: Segmentation and classification of elements into a hierarchic category system on the basis of defined relations.

Collaborative Tagging: The process of collaboratively assigning keywords to resources or items on the Internet.

Tags: Descriptive keywords which users attribute to online resources.

Semantic Web: Augmentation of online resources with unambiguous machine-readable descriptions of content or functions. While existing web resources are extended without modifying their original functionality, the boundary between human and automated understanding is abrogated.

Enterprise Tagging: The use of collaborative tagging in a corporate environment.

Ontology: Data model that constitutes a set of concepts within a domain. The model includes the relationships between those concepts as well as rules for inference and integrity.

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