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An evaluation of enhancing social tagging with a knowledge organization system

Authors: Brian Matthews; Catherine Mary Jones; Bartlomiej Puzon; Jim Moon; Douglas Tudhope; Koraljka Golub; Marianne Lykke Nielsen;

An evaluation of enhancing social tagging with a knowledge organization system

Abstract

PurposeTraditional subject indexing and classification are considered infeasible in many digital collections. This paper seeks to investigate ways of enhancing social tagging via knowledge organization systems, with a view to improving the quality of tags for increased information discovery and retrieval performance.Design/methodology/approachEnhanced tagging interfaces were developed for exemplar online repositories, and trials were undertaken with author and reader groups to evaluate the effectiveness of tagging augmented with control vocabulary for subject indexing of papers in online repositories.FindingsThe results showed that using a knowledge organisation system to augment tagging does appear to increase the effectiveness of non‐specialist users (that is, without information science training) in subject indexing.Research limitations/implicationsWhile limited by the size and scope of the trials undertaken, these results do point to the usefulness of a mixed approach in supporting the subject indexing of online resources.Originality/valueThe value of this work is as a guide to future developments in the practical support for resource indexing in online repositories.

Country
Sweden
Keywords

020, Knowledge management, Biblioteks- och informationsvetenskap, folksonomy, Information Studies, https://iskouk.org/subjects/00I8GP8X, Tagging, https://iskouk.org/subjects/PRUIHEDJ, https://iskouk.org/subjects/FVKXA4HR, knowledge organization system, Controlled languages, social tagging, Social groups, https://iskouk.org/subjects/MCBV57TL, controlled vocabulary, https://iskouk.org/subjects/16LVUVBG

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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