UMDSub at SemEval-2018 Task 2: Multilingual Emoji Prediction Multi-channel Convolutional Neural Network on Subword Embedding

Abstract

This paper describes the UMDSub system that participated in Task 2 of SemEval-2018. We developed a system that predicts an emoji given the raw text in a English tweet. The system is a Multi-channel Convolutional Neural Network based on subword embeddings for the representation of tweets. This model improves on character or word based methods by about 2\%. Our system placed 21st of 48 participating systems in the official evaluation.

arXiv comment5 pages, to Appear in the Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval 2018), June 2018, New Orleans, LA

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• Character-Aware Neural Language Models
• Enriching Word Vectors with Subword Information
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• Character-level and Multi-channel Convolutional Neural Networks for Large-scale Authorship Attribution