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2018 EMNLP EMNLP 2018

UTFPR at IEST 2018: Exploring Character-to-Word Composition for Emotion Analysis

Abstract

AbstractWe introduce the UTFPR system for the Implicit Emotions Shared Task of 2018: A compositional character-to-word recurrent neural network that does not exploit heavy and/or hard-to-obtain resources. We find that our approach can outperform multiple baselines, and offers an elegant and effective solution to the problem of orthographic variance in tweets.

🐣 Hot Topic Early Bird - tweet classification

Authors

Gustavo Paetzold

Topics

Machine Learning > Core Methods > Representation Learning Machine Learning > Application Areas > Data Augmentation Artificial Intelligence > Core AI > Natural Language Processing Deep Learning > Architectures > Recurrent Neural Networks

Keywords

sentiment analysis recurrent neural network character embedding character-level model emotion analysis compositional model tweet classification

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