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 651700 of 5630 papers

TitleStatusHype
Evaluating Zero-Shot Multilingual Aspect-Based Sentiment Analysis with Large Language ModelsCode0
Explain Thyself Bully: Sentiment Aided Cyberbullying Detection with ExplanationCode0
Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie ReviewsCode0
Entity-Level Sentiment Analysis (ELSA): An exploratory task surveyCode0
Enhancing Text Classification through LLM-Driven Active Learning and Human AnnotationCode0
An Effectiveness Metric for Ordinal Classification: Formal Properties and Experimental ResultsCode0
Enhancing TinyBERT for Financial Sentiment Analysis Using GPT-Augmented FinBERT DistillationCode0
Entity-Level Sentiment: More than the Sum of Its PartsCode0
An Effective Deployment of Diffusion LM for Data Augmentation in Low-Resource Sentiment ClassificationCode0
Improving Sequence Modeling Ability of Recurrent Neural Networks via SememesCode0
Enhancing Rhetorical Figure Annotation: An Ontology-Based Web Application with RAG IntegrationCode0
Adversarial Deep Averaging Networks for Cross-Lingual Sentiment ClassificationCode0
Enhancing Pharmacovigilance with Drug Reviews and Social MediaCode0
Enhancing Sentence Embedding with Generalized PoolingCode0
An Automated Text Categorization Framework based on Hyperparameter OptimizationCode0
An Aspect Extraction Framework using Different Embedding Types, Learning Models, and Dependency StructureCode0
Enhancing Event-Level Sentiment Analysis with Structured ArgumentsCode0
Enhancing Assamese NLP Capabilities: Introducing a Centralized Dataset RepositoryCode0
A Comprehensive Review on Hashtag Recommendation: From Traditional to Deep Learning and BeyondCode0
Enhancing Collaborative Filtering Recommender with Prompt-Based Sentiment AnalysisCode0
Enhanced Coherence-Aware Network with Hierarchical Disentanglement for Aspect-Category Sentiment AnalysisCode0
Enhancing Affinity Propagation for Improved Public Sentiment InsightsCode0
End-to-End Annotator Bias Approximation on Crowdsourced Single-Label Sentiment AnalysisCode0
Multi-task Pairwise Neural Ranking for Hashtag SegmentationCode0
Enhancing Inflation Nowcasting with LLM: Sentiment Analysis on NewsCode0
ERNIE-Doc: A Retrospective Long-Document Modeling TransformerCode0
Explicit Document Modeling through Weighted Multiple-Instance LearningCode0
HP-BERT: A framework for longitudinal study of Hinduphobia on social media via LLMsCode0
An analysis of vaccine-related sentiments from development to deployment of COVID-19 vaccinesCode0
Emoji Prediction in Tweets using BERTCode0
emojiSpace: Spatial Representation of EmojisCode0
Emoji-Based Transfer Learning for Sentiment TasksCode0
Emoji-Powered Representation Learning for Cross-Lingual Sentiment ClassificationCode0
Emo2Vec: Learning Generalized Emotion Representation by Multi-task TrainingCode0
Analyzing sports commentary in order to automatically recognize events and extract insightsCode0
emoji2vec: Learning Emoji Representations from their DescriptionCode0
EFSA: Towards Event-Level Financial Sentiment AnalysisCode0
Efficient Vector Representation for Documents through CorruptionCode0
ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment AnalysisCode0
Embedding Projection for Targeted Cross-Lingual Sentiment: Model Comparisons and a Real-World StudyCode0
Efficient Low-rank Multimodal Fusion with Modality-Specific FactorsCode0
Leveraging Encoder-only Large Language Models for Mobile App Review Feature ExtractionCode0
Advancing NLP with Cognitive Language Processing SignalsCode0
Effective Use of Word Order for Text Categorization with Convolutional Neural NetworksCode0
Efficient Sentiment Analysis: A Resource-Aware Evaluation of Feature Extraction Techniques, Ensembling, and Deep Learning ModelsCode0
Embeddings for Word Sense Disambiguation: An Evaluation StudyCode0
EmotionGIF-Yankee: A Sentiment Classifier with Robust Model Based Ensemble MethodsCode0
Analyzing Language Bias Between French and English in Conventional Multilingual Sentiment Analysis ModelsCode0
E2TP: Element to Tuple Prompting Improves Aspect Sentiment Tuple PredictionCode0
Economy Watchers Survey Provides Datasets and Tasks for Japanese Financial DomainCode0
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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