ABSA-PyTorch

Aspect Based Sentiment Analysis with PyTorch.

基于侧面的情感分析问题，PyTorch实现。

Dependencies

• PyTorch 0.4.0
• tensorboardX 1.2
• Python 3.6
• Pre-trained word vectors (See data_utils.py for more detail)
  • Download pre-trained Twitter word vectors here,
  • extract the glove.twitter.27B.zip and glove.42B.300d.zip to the root directory

An usage example

Training

python lstm.py

See the training process (needs to install TensorFlow)

tensorboard --logdir=./lstm_logs

Reviews / Surveys

Zhang, Lei, Shuai Wang, and Bing Liu. "Deep Learning for Sentiment Analysis: A Survey." arXiv preprint arXiv:1801.07883 (2018). [pdf]

Young, Tom, et al. "Recent trends in deep learning based natural language processing." arXiv preprint arXiv:1708.02709 (2017). [pdf]

Papers & Models

RAM (ram.py)

Chen, Peng, et al. "Recurrent Attention Network on Memory for Aspect Sentiment Analysis." Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. 2017. [pdf]

MemNet (memnet.py)

Tang, Duyu, Bing Qin, and Ting Liu. "Aspect level sentiment classification with deep memory network." arXiv preprint arXiv:1605.08900 (2016). [pdf]

IAN

Ma, Dehong, et al. "Interactive Attention Networks for Aspect-Level Sentiment Classification." arXiv preprint arXiv:1709.00893 (2017).

TD-LSTM (td_lstm.py)

Tang, Duyu, et al. "Effective LSTMs for Target-Dependent Sentiment Classification." Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers. 2016. [pdf]

LSTM (lstm.py)

Licence

MIT License