SOTAVerified

Sentiment Analysis

Sentiment Analysis is the task of classifying the polarity of a given text. For instance, a text-based tweet can be categorized into either "positive", "negative", or "neutral". Given the text and accompanying labels, a model can be trained to predict the correct sentiment.

Sentiment Analysis techniques can be categorized into machine learning approaches, lexicon-based approaches, and even hybrid methods. Some subcategories of research in sentiment analysis include: multimodal sentiment analysis, aspect-based sentiment analysis, fine-grained opinion analysis, language specific sentiment analysis.

More recently, deep learning techniques, such as RoBERTa and T5, are used to train high-performing sentiment classifiers that are evaluated using metrics like F1, recall, and precision. To evaluate sentiment analysis systems, benchmark datasets like SST, GLUE, and IMDB movie reviews are used.

Further readings:

Papers

Showing 33513400 of 5630 papers

TitleStatusHype
A Hybrid Approach for Aspect-Based Sentiment Analysis Using a Lexicalized Domain Ontology and Attentional Neural ModelsCode0
Incorporating End-to-End Speech Recognition Models for Sentiment Analysis0
Cooperative Learning of Disjoint Syntax and SemanticsCode0
Attentional Encoder Network for Targeted Sentiment ClassificationCode0
Star-TransformerCode0
Transfer Learning for Sequences via Learning to Collocate0
VCWE: Visual Character-Enhanced Word EmbeddingsCode0
Leveraging Deep Graph-Based Text Representation for Sentiment Polarity Applications0
Vector of Locally-Aggregated Word Embeddings (VLAWE): A Novel Document-level RepresentationCode0
Aspect-Sentiment Embeddings for Company Profiling and Employee Opinion Mining0
Stacking with Neural network for Cryptocurrency investment0
Investigating the Effect of Segmentation Methods on Neural Model based Sentiment Analysis on Informal Short Texts in Turkish0
Data augmentation for low resource sentiment analysis using generative adversarial networks0
A Comparative Study of Feature Selection Methods for Dialectal Arabic Sentiment Classification Using Support Vector MachineCode0
Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media0
Categorical Metadata Representation for Customized Text ClassificationCode0
The Many-to-Many Mapping Between the Concordance Correlation Coefficient and the Mean Square ErrorCode0
Predicting US State-Level Agricultural Sentiment as a Measure of Food Security with Tweets from Farming Communities0
Multi-task Learning for Target-dependent Sentiment ClassificationCode0
Tensor Variable Elimination for Plated Factor Graphs0
Towards Autoencoding Variational Inference for Aspect-based Opinion SummaryCode0
Aspect Specific Opinion Expression Extraction using Attention based LSTM-CRF Network0
Word Embeddings for Sentiment Analysis: A Comprehensive Empirical Survey0
Natural Language Processing, Sentiment Analysis and Clinical Analytics0
Multi-Task Deep Neural Networks for Natural Language UnderstandingCode0
Tensorized Embedding Layers for Efficient Model CompressionCode0
Glyce: Glyph-vectors for Chinese Character RepresentationsCode0
Language Independent Sequence Labelling for Opinion Target Extraction0
Squeezed Very Deep Convolutional Neural Networks for Text ClassificationCode0
How is Your Mood When Writing Sexist tweets? Detecting the Emotion Type and Intensity of Emotion Using Natural Language Processing Techniques0
Intrinsically Sparse Long Short-Term Memory Networks0
Language Model Pre-training for Hierarchical Document Representations0
Subspace Clustering of Very Sparse High-Dimensional Data0
State-Regularized Recurrent Neural Networks0
Squared English Word: A Method of Generating Glyph to Use Super Characters for Sentiment Analysis0
Deep Neural Linear Bandits: Overcoming Catastrophic Forgetting through Likelihood Matching0
A review of sentiment computation methods with R packages0
Emotion Detection and Analysis on Social Media0
Sentiment and Sarcasm Classification with Multitask Learning0
Phonetic-enriched Text Representation for Chinese Sentiment Analysis with Reinforcement Learning0
Delta-training: Simple Semi-Supervised Text Classification using Pretrained Word EmbeddingsCode0
Sentiment Analysis of Czech Texts: An Algorithmic Survey0
Aspect Category Detection via Topic-Attention Network0
Sentence-Level Sentiment Analysis of Financial News Using Distributed Text Representations and Multi-Instance Learning0
Sentiment Classification of Customer Reviews about Automobiles in Roman Urdu0
CAN: Constrained Attention Networks for Multi-Aspect Sentiment Analysis0
Supervised Sentiment Classification with CNNs for Diverse SE DatasetsCode0
Found in Translation: Learning Robust Joint Representations by Cyclic Translations Between ModalitiesCode0
Unifying Topic, Sentiment & Preference in an HDP-Based Rating Regression Model for Online ReviewsCode0
An Empirical Evaluation of Sketched SVD and its Application to Leverage Score Ordering0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Word+ES (Scratch)Attack Success Rate100Unverified
2MT-DNN-SMARTAccuracy97.5Unverified
3T5-11BAccuracy97.5Unverified
4MUPPET Roberta LargeAccuracy97.4Unverified
5T5-3BAccuracy97.4Unverified
6ALBERTAccuracy97.1Unverified
7StructBERTRoBERTa ensembleAccuracy97.1Unverified
8XLNet (single model)Accuracy97Unverified
9SMARTRoBERTaDev Accuracy96.9Unverified
10ELECTRAAccuracy96.9Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-large with LlamBERTAccuracy96.68Unverified
2RoBERTa-largeAccuracy96.54Unverified
3XLNetAccuracy96.21Unverified
4Heinsen Routing + RoBERTa LargeAccuracy96.2Unverified
5RoBERTa-large 355M + Entailment as Few-shot LearnerAccuracy96.1Unverified
6GraphStarAccuracy96Unverified
7DV-ngrams-cosine with NB sub-sampling + RoBERTa.baseAccuracy95.94Unverified
8DV-ngrams-cosine + RoBERTa.baseAccuracy95.92Unverified
9Roberta_Large ST + Cosine Similarity LossAccuracy95.9Unverified
10BERT large finetune UDAAccuracy95.8Unverified
#ModelMetricClaimedVerifiedStatus
1Llama-3.3-70B + CAPOAccuracy62.27Unverified
2Mistral-Small-24B + CAPOAccuracy 60.2Unverified
3Heinsen Routing + RoBERTa LargeAccuracy59.8Unverified
4RoBERTa-large+Self-ExplainingAccuracy59.1Unverified
5Qwen2.5-32B + CAPOAccuracy 59.07Unverified
6Heinsen Routing + GPT-2Accuracy58.5Unverified
7BCN+Suffix BiLSTM-Tied+CoVeAccuracy56.2Unverified
8BERT LargeAccuracy55.5Unverified
9LM-CPPF RoBERTa-baseAccuracy54.9Unverified
10BCN+ELMoAccuracy54.7Unverified
#ModelMetricClaimedVerifiedStatus
1Char-level CNNError4.88Unverified
2SVDCNNError4.74Unverified
3LEAMError4.69Unverified
4fastText, h=10, bigramError4.3Unverified
5SWEM-hierError4.19Unverified
6SRNNError3.96Unverified
7M-ACNNError3.89Unverified
8DNC+CUWError3.6Unverified
9CCCapsNetError3.52Unverified
10Block-sparse LSTMError3.27Unverified
#ModelMetricClaimedVerifiedStatus
1Millions of EmojiTraining Time1,500Unverified
2VLAWEAccuracy93.3Unverified
3RoBERTa-large 355M + Entailment as Few-shot LearnerAccuracy92.5Unverified
4AnglE-LLaMA-7BAccuracy91.09Unverified
5byte mLSTM7Accuracy86.8Unverified
6MEANAccuracy84.5Unverified
7RNN-CapsuleAccuracy83.8Unverified
8Capsule-BAccuracy82.3Unverified
9SuBiLSTM-TiedAccuracy81.6Unverified
10USE_T+CNNAccuracy81.59Unverified