Abstract
In this paper we show how the performance of tweet clustering can be improved by leveraging character-based neural networks. The proposed approach overcomes the limitations related to the vocabulary explosion in the word-based models and allows for the seamless processing of the multilingual content. Our evaluation results and code are available on-line: https://github.com/vendi12/tweet2vec_clustering.- Anthology ID:
- W17-1105
- Volume:
- Proceedings of the Fifth International Workshop on Natural Language Processing for Social Media
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- Lun-Wei Ku, Cheng-Te Li
- Venue:
- SocialNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 36–44
- Language:
- URL:
- https://aclanthology.org/W17-1105
- DOI:
- 10.18653/v1/W17-1105
- Cite (ACL):
- Svitlana Vakulenko, Lyndon Nixon, and Mihai Lupu. 2017. Character-based Neural Embeddings for Tweet Clustering. In Proceedings of the Fifth International Workshop on Natural Language Processing for Social Media, pages 36–44, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- Character-based Neural Embeddings for Tweet Clustering (Vakulenko et al., SocialNLP 2017)
- PDF:
- https://preview.aclanthology.org/revert-3132-ingestion-checklist/W17-1105.pdf
- Code
- vendi12/tweet2vec_clustering