Target-dependent sentiment classification in news articles reporting on political events. Includes a high-quality data set of over 11k sentences and a state-of-the-art classification model.
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Our GRU-TSC model for target-dependent sentiment classification in news articles. We employ the pre-trained RoBERTa language model in a Bi-GRU architecture and fine-tuned it on NewsMTSC.