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Lecture Notes in Computer Science
In the dominance of social networks era, vast information is created and shared across the world each day. The uniqueness and the prevalence of these user-generated content present both challenges and opportunities. In this thesis, in particular, we study several tasks on mining the user-generated content with regard to textual content and link-based content. First, we study the home location estimation for Twitter users from their shared textual content. We employ Gaussian Mixture Model todoi:10.1007/978-3-642-12275-0_22 fatcat:ou4wo4a6efdabkipzbkaxd5cyi