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In this paper, we describe our participation in the first shared task on automated stance detection (SemEval 2016 Task 6). We consider the task as a multidimensional classification problem and thus use a sequence of stacked classifiers. For subtask A, we utilize a rich feature set that does not rely on external information such as additional tweets or knowledge bases. For subtask B, we rely on the similarity of tweets in this task with tweets from subtask A in order to transfer the models learnt in subtask A.

ltl.uni-due at SemEval-2016 Task 6: Stance Detection in Social Media Using Stacked Classifiers