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In this paper, we present work on extracting social networks from unstructured text. We introduce novel features derived from semantic annotations based on FrameNet. We also introduce novel semantic tree kernels that help us improve the performance of the best reported system on social event detection and classification by a statistically significant margin. We show results for combining the models for the two aforementioned subtasks into the overall task of social network extraction. We show that a combination of features from all three levels of abstractions (lexical, syntactic and semantic) are required to achieve the best performing system.

Frame Semantic Tree Kernels for Social Network Extraction from Text