The Structure of Collaborative Tagging Systems

TLDR

Collaborative tagging is a user-driven process where many individuals add keyword metadata to shared content, and its popularity has surged on web platforms for bookmarks, photos, and other media. The study analyzes the structure and dynamical aspects of collaborative tagging systems. The authors develop a dynamical model of collaborative tagging that predicts stable tag patterns and links them to imitation and shared knowledge. The analysis revealed regularities in user activity, tag frequencies, tag types, popularity bursts, and a remarkable stability in tag proportions within URLs, which the model successfully predicts.

Abstract

Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs and other content. In this paper we analyze the structure of collaborative tagging systems as well as their dynamical aspects. Specifically, we discovered regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given url. We also present a dynamical model of collaborative tagging that predicts these stable patterns and relates them to imitation and shared knowledge.