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.
R. Cañamares, and P. Castells. Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM, (August 2017)
X. He, L. Liao, H. Zhang, L. Nie, X. Hu, and T. Chua. Proceedings of the 26th International Conference on World Wide Web, page 173–182. Republic and Canton of Geneva, CHE, International World Wide Web Conferences Steering Committee, (2017)
F. Ma, W. Wang, and Z. Deng. Social Media Retrieval and Mining, volume 387 of Communications in Computer and Information Science, Springer, Berlin/Heidelberg, (2013)
M. O'Connor, and J. Herlocker. Proceedings of the ACM SIGIR Workshop on Recommender Systems: Algorithms and Evaluation, Berkeley, California, USA, (August 1999)