Character-based Neural Embeddings for Tweet Clustering

Svitlana Vakulenko, Lyndon Nixon, Mihai Lupu


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
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/W17-1105.pdf
Code
 vendi12/tweet2vec_clustering