Sentiment Analysis
Sentiment analysis is the task of classifying the polarity of a given text.
State-of-the-art leaderboards
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Subtasks
Greatest papers with code
Adversarial Training Methods for Semi-Supervised Text Classification
Adversarial training provides a means of regularizing supervised learning algorithms while virtual adversarial training is able to extend supervised learning algorithms to the semi-supervised setting.
#7 best model for
Sentiment Analysis
on IMDb
Effective Use of Word Order for Text Categorization with Convolutional Neural Networks
HLT 2015
• tensorflow/models
• 
Convolutional neural network (CNN) is a neural network that can make use of the internal structure of data such as the 2D structure of image data.
#8 best model for
Sentiment Analysis
on IMDb
Bag of Tricks for Efficient Text Classification
EACL 2017 • facebookresearch/fastText
This paper explores a simple and efficient baseline for text classification.
SOTA for Sentiment Analysis on Sogou News
XLNet: Generalized Autoregressive Pretraining for Language Understanding
• huggingface/pytorch-pretrained-BERT
• 
With the capability of modeling bidirectional contexts, denoising autoencoding based pretraining like BERT achieves better performance than pretraining approaches based on autoregressive language modeling.
DOCUMENT RANKING LANGUAGE MODELLING NATURAL LANGUAGE INFERENCE QUESTION ANSWERING READING COMPREHENSION SEMANTIC TEXTUAL SIMILARITY SENTIMENT ANALYSIS TEXT CLASSIFICATION
Deep contextualized word representations
NAACL 2018
• zalandoresearch/flair
•
We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e. g., syntax and semantics), and (2) how these uses vary across linguistic contexts (i. e., to model polysemy).
#3 best model for
Sentiment Analysis
on SST-5 Fine-grained classification
CITATION INTENT CLASSIFICATION COREFERENCE RESOLUTION LANGUAGE MODELLING NAMED ENTITY RECOGNITION NATURAL LANGUAGE INFERENCE QUESTION ANSWERING SEMANTIC ROLE LABELING SENTIMENT ANALYSIS
Convolutional Neural Networks for Sentence Classification
EMNLP 2014
• dennybritz/cnn-text-classification-tf
•
We report on a series of experiments with convolutional neural networks (CNN) trained on top of pre-trained word vectors for sentence-level classification tasks.
A Structured Self-attentive Sentence Embedding
• jadore801120/attention-is-all-you-need-pytorch
•
This paper proposes a new model for extracting an interpretable sentence embedding by introducing self-attention.
NATURAL LANGUAGE INFERENCE SENTENCE EMBEDDING SENTIMENT ANALYSIS
Character-level Convolutional Networks for Text Classification
NeurIPS 2015
• gaussic/text-classification-cnn-rnn
•
This article offers an empirical exploration on the use of character-level convolutional networks (ConvNets) for text classification.
#12 best model for
Sentiment Analysis
on Yelp Fine-grained classification
The Natural Language Decathlon: Multitask Learning as Question Answering
ICLR 2019
• salesforce/decaNLP
•
Though designed for decaNLP, MQAN also achieves state of the art results on the WikiSQL semantic parsing task in the single-task setting.
DOMAIN ADAPTATION MACHINE TRANSLATION NAMED ENTITY RECOGNITION NATURAL LANGUAGE INFERENCE QUESTION ANSWERING RELATION EXTRACTION SEMANTIC PARSING SEMANTIC ROLE LABELING SENTIMENT ANALYSIS TEXT CLASSIFICATION TRANSFER LEARNING
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
IJCNLP 2015
• tensorflow/fold
•
Because of their superior ability to preserve sequence information over time, Long Short-Term Memory (LSTM) networks, a type of recurrent neural network with a more complex computational unit, have obtained strong results on a variety of sequence modeling tasks.