MeSH versus BibSonomy: A Comparative Study of Index Terms and Social Tags in Nursing Literature

Abstract

Present study attempts to examine similarities and differences between the expert generated subject headings and social tags. The study focuses on the comparing BibSonomy social tags and MeSH terms. For this purpose hundred articles in the domain of nursing were collected from BibSonomy as well as PuMed. The results show that 92.72% MeSH terms are not available in social tag vocabulary and almost 15% social tags are likely to be accepted by MeSH terms i.e., experts. Jaccard similarity coefficient shows that users and experts use variant terminology. Users use mostly title-based keywords while experts have used mostly topic-based terminologies. It is suggested that while social tags could improve document retrieval. They cannot substitute controlled vocabulary. OPACs must allow users to describe library documents through user-generated social tags along with expert (librarian) generated terms.