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 29012950 of 5630 papers

TitleStatusHype
Aspect Term Extraction using Graph-based Semi-Supervised Learning0
A Systematic Comparison of Architectures for Document-Level Sentiment ClassificationCode0
Multilogue-Net: A Context Aware RNN for Multi-modal Emotion Detection and Sentiment Analysis in ConversationCode1
An enhanced Tree-LSTM architecture for sentence semantic modeling using typed dependencies0
Robustness Verification for TransformersCode1
Towards Detection of Subjective Bias using Contextualized Word EmbeddingsCode0
Convolutional Neural Networks for Sentiment Analysis in Persian Social Media0
Sentiment Analysis Using Averaged Weighted Word Vector FeaturesCode0
Utilizing BERT Intermediate Layers for Aspect Based Sentiment Analysis and Natural Language InferenceCode1
Performance Comparison of Crowdworkers and NLP Tools on Named-Entity Recognition and Sentiment Analysis of Political Tweets0
Description Based Text Classification with Reinforcement Learning0
Related Tasks can Share! A Multi-task Framework for Affective language0
GIM: Gaussian Isolation Machines0
Deriving Emotions and Sentiments from Visual Content: A Disaster Analysis Use Case0
Improving Domain-Adapted Sentiment Classification by Deep Adversarial Mutual LearningCode1
Learning to Detect Malicious Clients for Robust Federated Learning0
Hybrid Tiled Convolutional Neural Networks for Text Sentiment Classification0
FastWordBug: A Fast Method To Generate Adversarial Text Against NLP Applications0
Adversarial Training for Aspect-Based Sentiment Analysis with BERTCode1
Multi-modal Sentiment Analysis using Super Characters Method on Low-power CNN Accelerator Device0
Emotion and Sentiment Lexicon Impact on Sentiment Analysis Applied to Book Reviews0
ARAACOM: ARAbic Algerian Corpus for Opinion Mining0
Sequence Labeling Approach to the Task of Sentence Boundary DetectionCode0
Unsupervised Sentiment Analysis for Code-mixed DataCode0
RobBERT: a Dutch RoBERTa-based Language ModelCode1
Predictive analysis of Bitcoin price considering social sentimentsCode1
Knowledge Discovery from Social Media using Big Data provided Sentiment Analysis (SoMABiT)0
A BERT based Sentiment Analysis and Key Entity Detection Approach for Online Financial Texts0
Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits0
Multi-source Domain Adaptation for Visual Sentiment Classification0
Latent Opinions Transfer Network for Target-Oriented Opinion Words ExtractionCode1
Generating Word and Document Embeddings for Sentiment Analysis0
Adapting Deep Learning for Sentiment Classification of Code-Switched Informal Short TextCode0
Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data0
Using Extractive Lexicon-based Sentiment Analysis to Enhance Understanding ofthe Impact of Non-GAAP Measures in Financial Reporting0
Target-Guided Structured Attention Network for Target-Dependent Sentiment Analysis0
Corpus Based Amharic Sentiment Lexicon Generation0
Evidence of disorientation towards immunization on online social media after contrasting political communication on vaccines. Results from an analysis of Twitter data in Italy0
Revisiting Paraphrase Question Generator using Pairwise DiscriminatorCode0
Dirichlet uncertainty wrappers for actionable algorithm accuracy accountability and auditability0
Language Independent Sentiment Analysis0
Text Classification for Azerbaijani Language Using Machine Learning and Embedding0
Simultaneous Identification of Tweet Purpose and Position0
Discovering Protagonist of Sentiment with Aspect Reconstructed Capsule Network0
T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted AttackCode1
BERTje: A Dutch BERT ModelCode1
A Heterogeneous Graphical Model to Understand User-Level Sentiments in Social Media0
A Multi-task Learning Model for Chinese-oriented Aspect Polarity Classification and Aspect Term ExtractionCode2
Artificial mental phenomena: Psychophysics as a framework to detect perception biases in AI models0
SemEval-2013 Task 2: Sentiment Analysis in Twitter0
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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