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Social networks have become a popular medium for people to communicate and distribute ideas, content, news and advertisements. Social content annotation has naturally emerged as a method of categorization and filtering of online information. The unrestricted vocabulary users choose from to annotate content has often lead to an explosion of the size of space in which search is performed. In this article, we propose latent topic models as a principled way of reducing the dimensionality of suchdoi:10.1145/2516891 fatcat:mticr2ax4bdffp6hpt6ty632ri