NTUA-SLP at SemEval-2018 Task 2: Predicting Emojis using RNNs with Context-aware Attention
Christos Baziotis, Athanasiou Nikolaos, Athanasia Kolovou, Georgios Paraskevopoulos, Nikolaos Ellinas, Alexandros Potamianos
Abstract
In this paper we present a deep-learning model that competed at SemEval-2018 Task 2 “Multilingual Emoji Prediction”. We participated in subtask A, in which we are called to predict the most likely associated emoji in English tweets. The proposed architecture relies on a Long Short-Term Memory network, augmented with an attention mechanism, that conditions the weight of each word, on a “context vector” which is taken as the aggregation of a tweet’s meaning. Moreover, we initialize the embedding layer of our model, with word2vec word embeddings, pretrained on a dataset of 550 million English tweets. Finally, our model does not rely on hand-crafted features or lexicons and is trained end-to-end with back-propagation. We ranked 2nd out of 48 teams.- Anthology ID:
- S18-1069
- Volume:
- Proceedings of the 12th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Venues:
- SemEval | *SEM
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 438–444
- Language:
- URL:
- https://aclanthology.org/S18-1069
- DOI:
- 10.18653/v1/S18-1069
- Cite (ACL):
- Christos Baziotis, Athanasiou Nikolaos, Athanasia Kolovou, Georgios Paraskevopoulos, Nikolaos Ellinas, and Alexandros Potamianos. 2018. NTUA-SLP at SemEval-2018 Task 2: Predicting Emojis using RNNs with Context-aware Attention. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 438–444, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- NTUA-SLP at SemEval-2018 Task 2: Predicting Emojis using RNNs with Context-aware Attention (Baziotis et al., SemEval-*SEM 2018)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/S18-1069.pdf
- Code
- additional community code