UMDSub at SemEval-2018 Task 2: Multilingual Emoji Prediction Multi-channel Convolutional Neural Network on Subword Embedding
This work addresses a specific natural language processing task for social media analysis, but it is incremental as it builds on existing methods with a modest performance gain.
The paper tackled emoji prediction from English tweets using a multi-channel convolutional neural network based on subword embeddings, achieving about a 2% improvement over character or word-based methods and placing 21st out of 48 systems in the SemEval-2018 competition.
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.