Analysis of keyword‐based tagging behaviors of experts and novices

Purpose – Expert and novice readers tag documents with different descriptions; this study is intended to discover which readers would generate the most reliable and most representative sets of tags. Design/methodology/approach – One group of experts and one group of novices were recruited. These two groups were asked to provide tags for document bookmarks in a Mozilla Firefox browser. In the experimental analysis we defined two measures – similarity and relevance – to describe the differences between the two groups. Findings – Tags chosen by experts yielded better similarity and relevance values in all analyses. Tags chosen by the expert group had higher commonality in pairwise similarity analysis; moreover, the relevance analysis showed that tags chosen by experts reflected better understanding of the content. Originality/value – Tagging behavior has become highly popular on the web, and its study has commercial merit. Tags from experts represent the structure behind the knowledge involved; expert representation may be vastly more helpful than novice representation for promoting understanding of content in an era characterized by an explosion of information.