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 32013250 of 5630 papers

TitleStatusHype
Low-Shot Classification: A Comparison of Classical and Deep Transfer Machine Learning Approaches0
Multi-modal Sentiment Analysis using Deep Canonical Correlation Analysis0
A Scalable Framework for Multilevel Streaming Data Analytics using Deep Learning0
Smile, Be Happy :) Emoji Embedding for Visual Sentiment Analysis0
ScenarioSA: A Large Scale Conversational Database for Interactive Sentiment Analysis0
Neural Networks as Explicit Word-Based Rules0
Sentiment Analysis Challenges in Persian Language0
Multimodal Fusion with Deep Neural Networks for Audio-Video Emotion Recognition0
A Study of the Effect of Resolving Negation and Sentiment Analysis in Recognizing Text Entailment for Arabic0
SEntiMoji: An Emoji-Powered Learning Approach for Sentiment Analysis in Software EngineeringCode0
Deep neural network-based classification model for Sentiment Analysis0
Neural Image Captioning0
Discourse Analysis and Its Applications0
Plongements lexicaux sp\'ecifiques \`a la langue arabe : application \`a l'analyse d'opinions (Arabic-specific embedddings : application in Sentiment Analysis)0
Sentiment Classification Using Document Embeddings Trained with Cosine SimilarityCode0
Latent Structure Models for Natural Language Processing0
Stochastic Tokenization with a Language Model for Neural Text Classification0
On the Robustness of Self-Attentive Models0
Sentiment Analysis on Naija-Tweets0
Reinforced Training Data Selection for Domain Adaptation0
Tree Communication Models for Sentiment AnalysisCode0
Can Modern Standard Arabic Approaches be used for Arabic Dialects? Sentiment Analysis as a Case Study0
Investigating Political Herd Mentality: A Community Sentiment Based Approach0
Transfer Capsule Network for Aspect Level Sentiment ClassificationCode0
Attention and Lexicon Regularized LSTM for Aspect-based Sentiment AnalysisCode0
Aspect Sentiment Classification Towards Question-Answering with Reinforced Bidirectional Attention Network0
Task Refinement Learning for Improved Accuracy and Stability of Unsupervised Domain AdaptationCode0
Deep Bayesian Natural Language Processing0
Advances in Argument Mining0
De-Mixing Sentiment from Code-Mixed Text0
Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization0
Latent Variable Sentiment GrammarCode0
FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithmsCode0
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics0
Embedding Projection for Targeted Cross-Lingual Sentiment: Model Comparisons and a Real-World StudyCode0
Good Secretaries, Bad Truck Drivers? Occupational Gender Stereotypes in Sentiment AnalysisCode0
Learning Latent Trees with Stochastic Perturbations and Differentiable Dynamic ProgrammingCode0
Systematic improvement of user engagement with academic titles using computational linguistics0
BERT-based Financial Sentiment Index and LSTM-based Stock Return Predictability0
Graph Star Net for Generalized Multi-Task LearningCode0
A New Statistical Approach for Comparing Algorithms for Lexicon Based Sentiment Analysis0
Citizens' Emotion on GST: A Spatio-Temporal Analysis over Twitter Data0
Unsupervised machine learning to analyse city logistics through Twitter0
Curriculum Learning Strategies for Hindi-English Codemixed Sentiment Analysis0
Improving Sentiment Analysis with Multi-task Learning of NegationCode0
Context-aware Embedding for Targeted Aspect-based Sentiment Analysis0
On the Effect of Word Order on Cross-lingual Sentiment Analysis0
Sentiment analysis is not solved! Assessing and probing sentiment classificationCode0
Modeling Sentiment Dependencies with Graph Convolutional Networks for Aspect-level Sentiment ClassificationCode0
Using Structured Representation and Data: A Hybrid Model for Negation and Sentiment in Customer Service Conversations0
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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