The Structure of Collaborative Tagging Systems

By Scott A. Golder, Bernardo A. Huberman. arXiv.org, 2005

1,067 citations recorded by the source corpus.

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.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/cf611e7a9c279e98220291d55c035c01eeecee09

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In Artificial Intelligence

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Citations in the corpus

A Survey of Crowdsourcing Systems (2011, background): “us7 is a social bookmark site on the Internet developed by Golder and Huberman[22].”
Tagsplanations: explaining recommendations using tags (2009, background): “As described in [5], tags may describe what an item is, what it is about, or what its characteristics are – all of which may be useful for explaining a recommendation.”
Concept-Based Video Retrieval (2009, background): “Since the labels were never meant to meet professional standards, amateur labels are known to be ambiguous, overly personalized, and limited [69] [73] [149].”
Exploring place through user-generated content: Using Flickr tags to describe city cores (2010, background): “The potential and drawbacks of content in tagging systems in terms of information organization and retrieval [14,39], the generation of ontologies [32], and its suitability to represent the perception of the individual [17], as well as distributed knowledge or the wisdom of the crowd [36,38] have…”
Integrating Folksonomies with the Semantic Web (2007, methodology): “As highlighted by Golder and Huberman (2005), the main problems of social tagging systems include ambiguity, lack of synonymy and discrepancies in granularity.”
Evaluating similarity measures for emergent semantics of social tagging (2009, background): “The tagging approach has several limitations including lack of structure [3], lack of global coherence [38], polysemy, and word semantics [15].”
Dogear: Social bookmarking in the enterprise (2006, result): “These correlations are stronger than those reported from an analysis of del.icio.us user [ 6 ].”
Flickr tag recommendation based on collective knowledge (2008, background): “A detailed account of different types of tagging systems can be found in [13] and [16].”
Tag recommendations based on tensor dimensionality reduction (2008, background): “In particular, Golder and Huberman [4] analyzed the structure of collaborative tagging systems as well as their dynamic aspects.”
Collaborative Creation of Communal Hierarchical Taxonomies in Social Tagging Systems (2006, background): “I. INTRODUCTION One of the lasting problems for CSCW in large scale organizations has been determining an effective way to not only store, but to allow users to annotate relevant data for future retrieval.”
Collaborative tagging as a knowledge organisation and resource discovery tool (2006, background): “In one of the few research studies to date, Golder and Huberman (2005) analysed data gathered from del.icio.us to better understand the structure of tagging systems, such as user activity, tag frequencies, the nature of tags used, and so forth.”
tagging, communities, vocabulary, evolution (2006, background): “As an extreme example, people who speak di.erent languages will .nd little value in each others tags.”
Getting our head in the clouds: toward evaluation studies of tagclouds (2007, background): “us [5], the flicker photo-sharing site [9], the LibraryThing book recommendation site (e.”
Semantic Wikipedia (2006, background): “us 16), pictures (flickr17), or even blog entries [11].”
Content-based Recommender Systems: State of the Art and Trends (2011, background): “Indeed, several difficulties of tagging systems have been identified, such as polysemy and synonymy of tags, or the different expertise and purposes of tagging participants that may result in tags at various levels of abstraction to describe a resource, or the chaotic proliferation of tags [40].”