Usage patterns of collaborative tagging systems

By Scott A. Golder, Bernardo A. Huberman. Journal of information science, 2006

2,115 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/70f85e852b00816188026808d8eaab8e068b9d03

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Citations in the corpus

Transparent, Scrutable and Explainable User Models for Personalized Recommendation (2019, background): “We further acknowledge that there are known issues regarding the quality [41] and redundancy [18] of social tags.”
Can social bookmarking improve web search? (2008, background): “[9] S. Golder and B. A. Huberman.”
Nonnegative shared subspace learning and its application to social media retrieval (2010, background): “NMF is also desirable for its ability to resolve the well-known ‘polysemy’ and ‘synonymy’ problems, known to exist in collaborative tagging applications which can cause performance degradation [8].”
Latent dirichlet allocation for tag recommendation (2009, background): “Thus, these tags can be inconsistent and idiosyncratic, both due to users’ personal terminology as well as due to the different purposes tags fulﬁll [15].”
Optimizing web search using social annotations (2007, background): “[27] analyzed the structure of collaborative tagging systems as well as their dynamical aspects.”
Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter (2010, background): “Tagging gained visibility with social bookmarking [6], but has expanded to other social media genres, including blogs.”
Friendship prediction and homophily in social media (2012, background): “Social media supporting tagging are especially relevant to a data-driven investigation of these questions, because they stimulate users to provide lightweight semantic annotations in the form of freely chosen terms [Golder and Huberman 2006].”
Human-competitive tagging using automatic keyphrase extraction (2009, background): “This leads to the greatest downside of tagging, inconsistency, which originates in the synonymy and polysemy of human language, as well as in the varying degrees of specificity used by taggers (Golder and Huberman, 2006).”
Content-based visual search learned from social media (2012, background): “Despite the success of social tagging, however, tags contributed by common users are known to be ambiguous, limited in terms of completeness, and overly personalized [39,81].”