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Abstract

The aim of this study is to analyse differences between tags on LibraryThing's web page and tag clouds in their "Library-Thing for Libraries" service, and assess if, and how, the Library-Thing tag moderation and limitations to the size of the tag cloud in the library catalogue affect the description of the information resource. An e-mail survey was conducted with personnel at LibraryThing, and the results were compared against tags for twenty different fiction books, collected from two different library catalogues with disparate tag cloud sizes, and Library-Thing's web page. The data were analysed using a modified version of Golder and Huberman's tag categories (2006). The results show that while LibraryThing claims to only remove the inherently personal tags, several other types of tags are found to have been discarded as well. Occasionally a certain type of tag is in-cluded in one book, and excluded in another. The comparison between the two tag cloud sizes suggests that the larger tag clouds provide a more pronounced picture regarding the contents of the book but at the cost of an increase in the number of tags with synonymous or redundant information.

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Abstract

Folksonomy, a free-form tagging, is a user-generated classification system of web contents that allows users to tag their favorite web resources with their chosen words or phrases selected from natural language. These tags (also called concepts, categories, facets or entities) can be used to classify web resources and to express users' preferences. Folksonomy-based systems allow users to classify web resources through tagging bookmarks, photos or other web resources and saving them to a public web site like Del.icio.us. Thus information about web resources and online articles can be shared in an easy way. The purpose of this study is to provide an overview of the folksonomy tagging phenomenon (also called social tagging and social bookmarking) and explore some of the reasons why we need controlled vocabularies, discussing the problems associated with folksonomy.

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Abstract

This article examines tagging as knowledge organization. Tagging is a kind of indexing, a process of labelling and categorizing information made to support resource discovery for users. Social tagging generally means the practice whereby internet users generate keywords to describe, categorise or comment on digital content. The value of tagging comes when social tags within a collection are aggregated and shared through a folksonomy. This article examines definitions of tagging and folksonomy, and discusses the functions, advantages and disadvantages of tagging systems in relation to knowledge organization before discussing studies that have compared tagging and conventional library-based knowledge organization systems. Approaches to disciplining tagging practice are examined and tagger motivation discussed. Finally, the article outlines current research fronts.

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Abstract

Purpose - The purpose of this paper is to investigate the linking of a folksonomy (user vocabulary) and LCSH (controlled vocabulary) on the basis of word matching, for the potential use of LCSH in bringing order to folksonomies. Design/methodology/approach - A selected sample of a folksonomy from a popular collaborative tagging system, Delicious, was word-matched with LCSH. LCSH was transformed into a tree structure called an LCSH tree for the matching. A close examination was conducted on the characteristics of folksonomies, the overlap of folksonomies with LCSH, and the distribution of folksonomies over the LCSH tree. Findings - The experimental results showed that the total proportion of tags being matched with LC subject headings constituted approximately two-thirds of all tags involved, with an additional 10 percent of the remaining tags having potential matches. A number of barriers for the linking as well as two areas in need of improving the matching are identified and described. Three important tag distribution patterns over the LCSH tree were identified and supported: skewedness, multifacet, and Zipfian-pattern. Research limitations/implications - The results of the study can be adopted for the development of innovative methods of mapping between folksonomy and LCSH, which directly contributes to effective access and retrieval of tagged web resources and to the integration of multiple information repositories based on the two vocabularies. Practical implications - The linking of controlled vocabularies can be applicable to enhance information retrieval capability within collaborative tagging systems as well as across various tagging system information depositories and bibliographic databases. Originality/value - This is among frontier works that examines the potential of linking a folksonomy, extracted from a collaborative tagging system, to an authority-maintained subject heading system. It provides exploratory data to support further advanced mapping methods for linking the two vocabularies.

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Abstract

Today I want to talk about categorization, and I want to convince you that a lot of what we think we know about categorization is wrong. In particular, I want to convince you that many of the ways we're attempting to apply categorization to the electronic world are actually a bad fit, because we've adopted habits of mind that are left over from earlier strategies. I also want to convince you that what we're seeing when we see the Web is actually a radical break with previous categorization strategies, rather than an extension of them. The second part of the talk is more speculative, because it is often the case that old systems get broken before people know what's going to take their place. (Anyone watching the music industry can see this at work today.) That's what I think is happening with categorization. What I think is coming instead are much more organic ways of organizing information than our current categorization schemes allow, based on two units -- the link, which can point to anything, and the tag, which is a way of attaching labels to links. The strategy of tagging -- free-form labeling, without regard to categorical constraints -- seems like a recipe for disaster, but as the Web has shown us, you can extract a surprising amount of value from big messy data sets.

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Source

Journal of the American Society for Information Science and Technology. 62(2011) no.3, S.478-492

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Abstract

Ontologies have been a hot research topic for the recent decade and have been used for many applications such as information integration, semantic search, knowledge management, etc. Manual engineering of ontologies is a costly process and automatic ontology engineering lacks in precision. Folksonomies have recently emerged as another hot research topic and several research efforts have been made to extract lightweight ontologies automatically from folksonomy data. Due to the high cost of manual ontology engineering and the lack of precision in automatic ontology engineering it is important that we are able to evaluate the structure of the ontology. Detection of problems with the suggested ontology at an early stage can, especially for manually engineered ontologies, be cost saving. In this paper we present an approach to evaluate the quality of hierarchical relations in ontologies and folksonomy based structures. The approach is based on constructing shallow semantic representations of the ontology concepts and folksonomy tags. We specify four hypotheses regarding the semantic representations and different quality aspects of the hierarchical relations and perform an evaluation on two different data sets. The results of the evaluation confirm our hypotheses.