Dana Movshovitz-Attias


2020

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GoEmotions: A Dataset of Fine-Grained Emotions
Dorottya Demszky | Dana Movshovitz-Attias | Jeongwoo Ko | Alan Cowen | Gaurav Nemade | Sujith Ravi
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Understanding emotion expressed in language has a wide range of applications, from building empathetic chatbots to detecting harmful online behavior. Advancement in this area can be improved using large-scale datasets with a fine-grained typology, adaptable to multiple downstream tasks. We introduce GoEmotions, the largest manually annotated dataset of 58k English Reddit comments, labeled for 27 emotion categories or Neutral. We demonstrate the high quality of the annotations via Principal Preserved Component Analysis. We conduct transfer learning experiments with existing emotion benchmarks to show that our dataset generalizes well to other domains and different emotion taxonomies. Our BERT-based model achieves an average F1-score of .46 across our proposed taxonomy, leaving much room for improvement.

2015

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KB-LDA: Jointly Learning a Knowledge Base of Hierarchy, Relations, and Facts
Dana Movshovitz-Attias | William W. Cohen
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

2013

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Natural Language Models for Predicting Programming Comments
Dana Movshovitz-Attias | William W. Cohen
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

2012

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Bootstrapping Biomedical Ontologies for Scientific Text using NELL
Dana Movshovitz-Attias | William W. Cohen
BioNLP: Proceedings of the 2012 Workshop on Biomedical Natural Language Processing

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Alignment-HMM-based Extraction of Abbreviations from Biomedical Text
Dana Movshovitz-Attias | William W. Cohen
BioNLP: Proceedings of the 2012 Workshop on Biomedical Natural Language Processing