Context-Sensitive Twitter Sentiment Classification Using Neural Network

Yafeng Ren, Yue Zhang, Meishan Zhang, Donghong Ji

AAAI 2016 pp. 215-221

doi:10.1609/AAAI.V30I1.9974 /aaai/2016/ren2016aaai-context/

Abstract

Sentiment classification on Twitter has attracted increasing research in recent years.Most existing work focuses on feature engineering according to the tweet content itself.In this paper, we propose a context-based neural network model for Twitter sentiment analysis, incorporating contextualized features from relevant Tweets into the model in the form of word embedding vectors.Experiments on both balanced and unbalanced datasets show that our proposed models outperform the current state-of-the-art.

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Cite

Text

Ren et al. "Context-Sensitive Twitter Sentiment Classification Using Neural Network." AAAI Conference on Artificial Intelligence, 2016. doi:10.1609/AAAI.V30I1.9974

Markdown

[Ren et al. "Context-Sensitive Twitter Sentiment Classification Using Neural Network." AAAI Conference on Artificial Intelligence, 2016.](https://mlanthology.org/aaai/2016/ren2016aaai-context/) doi:10.1609/AAAI.V30I1.9974

BibTeX

@inproceedings{ren2016aaai-context,
  title     = {{Context-Sensitive Twitter Sentiment Classification Using Neural Network}},
  author    = {Ren, Yafeng and Zhang, Yue and Zhang, Meishan and Ji, Donghong},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2016},
  pages     = {215-221},
  doi       = {10.1609/AAAI.V30I1.9974},
  url       = {https://mlanthology.org/aaai/2016/ren2016aaai-context/}
}