Tutorials
- SENTIMENT ANALYSIS OF TWITTER FEEDS by Yogesh Garg, Dr. Niladri Chatterjee: GitHub
- GitHub|Sentiment Analysis on Twitte
- Sentiment140 by okugami79: R package for Twitter sentiment text analysis: GitHub
- Quora|How do I use the sentiment140 data set for doing sentiment analysis in Python
- Sentiment Symposium Tutorial: Language and cognition by Christopher Potts, Stanford Linguistics, 2011: Homepage
- Emotion Detection and Recognition from Text Using Deep Learning
- List of Machine Learning and Deep Learning from GitHub: ZhiHu
- Twitter-Sentiment-Analysis: GitHub, Videos
- FFNN: feed-foward neural network: GitHub
- This is an obsolete package for neural networks. However, I believe this package helps beginners to implement neural networks in a low-level fashion. Hence, the package might still be useful for pedagogical purposes.
- By “feed-foward,” I mean that all other structures (e.g., recurrent, recursive, convolutional) are unrolled to a feed-forward net. Also included is an example with LSTM-based network for question classification.
- Resources for deep learning: papers, articles, courses: GitHub
- psyyz10/TextClassification.md: This document summarizes some potentially useful papers and code repositories on Sentiment analysis / document classification: GitHubGist
- char-rnn: This code implements multi-layer Recurrent Neural Network (RNN, LSTM, and GRU) for training/sampling from character-level language models: GitHub
- Sentiment Analysis with LSTMs: GitHub
- Keras examples directory: GitHub
- Stock Market prediction using news headlines by Joshua van Kleef, Valerie Scholten and Emiel Stoelinga: EmielStoelinga/CCMLWI
- Stock_Market_Prediction: GitHub
- Stock Predictor and Portfolio Optimizer: GitHub
- Financial Portfolio Optimization: GitHub
Tokenization
- Sentiment Tokenization Issues - Christopher Potts sentiment tokenizer Brendan
- Sentiment Tokenization Issues - O’Connor twitter tokenizer
Projects
- Social Media Data Mining on 2017 NBA Champ
- Sentiment Analysis on Reddit News Headlines with Python’s Natural Language Toolkit (NLTK)
- knowsuchagency/mpb-sentiment-analysis-example
- Sentiment Analysis of Reddit AMAs
- datumbox/twitter-sentiment-analysis
Tools
Codes & Packages & API
- Sentiment140 by by Alec Go, Richa Bhayani, and Lei Huang: Homepage
- Sentiment140 allows you to discover the sentiment of a brand, product, or topic on Twitter
- sentiment viz - Tweet Sentiment Visualization
- NLP at Cornell: Movie Review Data by Bo Pang or Lillian Lee: Homepage
- Stanford Deeply Moving: Deep Learning for Sentiment Analysis: GitHub, Paper
- SentiBank: Visual Sentiment Ontology: Homepage, Paper
- Lin, C., & He, Y. (2009, November). Joint sentiment/topic model for sentiment analysis. In Proceedings of the 18th ACM conference on Information and knowledge management (pp. 375-384). ACM.: GitHub, Paper
- Mesnil, G., Mikolov, T., Ranzato, M. A., & Bengio, Y. (2014). Ensemble of generative and discriminative techniques for sentiment analysis of movie reviews. arXiv preprint arXiv:1412.5335.: GitHub, Paper
- Hagen, M., Potthast, M., Büchner, M., & Stein, B. (2015, March). Twitter sentiment detection via ensemble classification using averaged confidence scores. In European Conference on Information Retrieval (pp. 741-754). Springer, Cham.: GitHub, Paper
- A comparison of open source tools for sentiment analysis: Page, GitHub
- Using Structured Events to Predict Stock Price Movement: An Empirical Investigation: GitHub, Paper
Document level/sentence level:
CNN-based
- A convolutional neural network for modelling sentences: GitHub
- Convolutional neural networks for sentence classification: GitHub
- Character-level Convolutional Networks for Text Classification: GitHub
- Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and Documents: GitHub
- Dependency-based Convolutional Neural Networks for Sentence Embedding: GitHub
- Discriminative Neural Sentence Modeling by Tree-Based Convolution
- Multichannel variable-size convolution for sentence classification.
RNN-based
- TOPICRNN: A RECURRENT NEURAL NETWORK WITH LONG-RANGE SEMANTIC DEPENDENCY
- Deep recursive neural networks for compositionality in language: Homepage, GitHub|deep-recursive
- Improved semantic representations from tree- structured long short-term memory networks
- Document modeling with gated recurrent neural network for sentiment classification: Paper, Videos
- Hierarchical Attention Networks for Document Classification: Github
- Semi-supervised Variational Autoencoders for Text Classification_aaai
- Semi-supervised Sequence Learning
- Yu, A. W., Lee, H., & Le, Q. V. (2017). Learning to skim text. arXiv preprint arXiv:1704.06877.: [Code]
- Neural Sentiment Classification with User and Product Attention: GitHub, Paper
MLP-based
- Deep Unordered Composition Rivals Syntactic Methods for Text Classification
- Bag of Tricks for Efficient Text Classification
Others
- Adversarial Multi-task Learning for Text Classification
- Harnessing Deep Neural Networks with Logic Rules
