Extracting Information from Social Media with GATE
K. Bontcheva⁎; L. Derczynski⁎ ⁎ University of Sheffield, Sheffield, UK
Abstract
Information extraction from social media content has only recently become an active research topic, following early experiments that showed this genre to be extremely challenging for state-of-the-art algorithms. Unlike carefully authored news text and other longer content, social media content poses a number of new challenges, due to shortness, noise, strong contextual anchoring, and highly dynamic nature.
This chapter provides a thorough analysis of the problems and describes the most recent GATE algorithms, specifically developed for extracting information from social media content. Comparisons against ...
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