DENS: A dataset for multi-class emotion analysis
Published in EMNLP, 2019
We introduce a new dataset for multi-class emotion analysis from long-form narratives in English. The Dataset for Emotions of Narrative Sequences (DENS) was collected from both classic literature available on Project Gutenberg and modern online narratives avail- able on Wattpad, annotated using Amazon Mechanical Turk. A number of statistics and baseline benchmarks are provided for the dataset. Of the tested techniques, we find that the fine-tuning of a pre-trained BERT model achieves the best results, with an average micro-F1 score of 60.4%. Our results show that the dataset provides a novel opportunity in emotion analysis that requires moving beyond existing sentence-level techniques.
Recommended citation: Chen Liu, Osama Muhammad, & Anderson de Andrade. (2019). "DENS: A dataset for multi-class emotion analysis." EMNLP.
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