Research: An Examination of Semantic Relationships Between Professionally Assigned Metadata and User-Generated Tags for Popular Literature in Complementary and Alternative Medicine

The article appears in the September 2011 Issue of Information Research.

Title: “Research: An Examination of Semantic Relationships Between Professionally Assigned Metadata and User-Generated Tags for Popular Literature in Complementary and Alternative Medicine”

Authors: Hemalata Iyer and Lucy Bungo
University at Albany, State University of New York, Department of Information Studies, College of Computing and Information, 135 Western Avenue, Albany, NY, USA, 12222

Abstract:

Introduction. This paper examines the semantic relationship between user tags and the assigned subject headings of popular literature in the domain of complementary and alternative medicine.
Method. Forty books in the domain were drawn from the LibraryThing database. These were qualitatively analysed for the semantic matches between user tags and subject headings. An adapted form of the Unified Medical Language System, Current Relations in the Semantic Network served as a framework for analysis.
Analysis. User tags were compared with subject headings for terminological matches on a book by book basis. The tags were grouped into tag categories, and tag categories were mapped on to the subject headings. Those that were not related to the subject headings were analysed for patterns.
Results. Less than 1% of tags matched terminologically. Results indicated 46% semantic matches and 54% non-matches. Frequently occurring patterns among non-matches were personal, genre or form, location, time period and belief systems. Of the semantic matches, frequently occurring relationships were physical, functional, and conceptual relationships.
Conclusions. The tag categories provide information beyond that of the subject headings; they describe, evaluate, and may assist readers in choosing materials. This study contributes towards an understanding of the dominant relationship types in this domain and this can feed into developing ontologies and knowledge structures.

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