deep-learning-sentiment-analysis is an NLP project that compares three different models for binary sentiment classification.
deep-learning-sentiment-analysis uses Stanford's [Large Movie Review Dataset] (http://ai.stanford.edu/~amaas/data/sentiment/). It consists of sets for positive train, negative train, positive test, and negative test, each of which has 12,500 reviews, along with 50,000 unlabeled reviews for unsupervised learning, for 100,000 total reviews. Each review is comprised of multiple sentences.
deep-learning-sentiment-analysis utilizes three different models for sentiment analysis:
- SentimentAnalysisCoreNLP.java: Recursive Neural Tensor Network via [Stanford CoreNLP] (http://nlp.stanford.edu/sentiment/code.html)
- sentiment_analysis_gensim.ipynb: Doc2Vec embedding via [gensim] (https://radimrehurek.com/gensim/models/doc2vec.html)
- sentiment_analysis_tensorflow.ipynb: Convolutional Neural network via [TensorFlow] (https://www.tensorflow.org/)
- Dataset: [Maas et al. 2011] (http://ai.stanford.edu/~amaas/papers/wvSent_acl2011.pdf)
- Recursive Neural Tensor Network: [Socher et al. 2013] (http://nlp.stanford.edu/~socherr/EMNLP2013_RNTN.pdf)
- Word2Vec: [Mikolov et al. 2013] (https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf)
- Doc2Vec: [Le and Mikolov 2014] (https://cs.stanford.edu/~quocle/paragraph_vector.pdf)
- Convolutional Neural Network: [Kim 2014] (https://arxiv.org/pdf/1408.5882v2.pdf)
deep-learning-sentiment-analysis is written in Python 2.7 in a Jupyter notebook and uses several common software libraries, most notably Stanford CoreNLP, gensim, and TensorFlow. In order to run it, you must install the follow dependencies:
- [Python] (https://www.python.org/)
- [Jupyter] (http://jupyter.org/)
- [Stanford CoreNLP] (http://stanfordnlp.github.io/CoreNLP/)
- [gensim] (https://radimrehurek.com/gensim/)
- [TensorFlow] (https://www.tensorflow.org/)
- [NumPy] (http://www.numpy.org/)
- [BeautifulSoup] (https://www.crummy.com/software/BeautifulSoup/)
This project uses the [Apache 2.0 License] (https://github.com/charlescc9/deep-learning-sentiment-analysis/blob/master/LICENSE).