ECNU: Multi-level Sentiment Analysis on Twitter Using Traditional Linguistic Features and Word Embedding Features

Zhihua Zhang, Guoshun Wu, Man Lan


Anthology ID:
S15-2094
Volume:
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)
Month:
June
Year:
2015
Address:
Denver, Colorado
Editors:
Preslav Nakov, Torsten Zesch, Daniel Cer, David Jurgens
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
561–567
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/S15-2094/
DOI:
10.18653/v1/S15-2094
Bibkey:
Cite (ACL):
Zhihua Zhang, Guoshun Wu, and Man Lan. 2015. ECNU: Multi-level Sentiment Analysis on Twitter Using Traditional Linguistic Features and Word Embedding Features. In Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), pages 561–567, Denver, Colorado. Association for Computational Linguistics.
Cite (Informal):
ECNU: Multi-level Sentiment Analysis on Twitter Using Traditional Linguistic Features and Word Embedding Features (Zhang et al., SemEval 2015)
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PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/S15-2094.pdf