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 22512300 of 5630 papers

TitleStatusHype
LSTM Based Sentiment Analysis for Cryptocurrency Prediction0
Drug Recommendation System based on Sentiment Analysis of Drug Reviews using Machine Learning0
When Word Embeddings Become Endangered0
A New Approach To Text Rating Classification Using Sentiment Analysis0
Exercise? I thought you said 'Extra Fries': Leveraging Sentence Demarcations and Multi-hop Attention for Meme Affect AnalysisCode0
Grey-box Adversarial Attack And Defence For Sentiment ClassificationCode0
L3CubeMahaSent: A Marathi Tweet-based Sentiment Analysis Dataset0
TextFlint: Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing0
Local Interpretations for Explainable Natural Language Processing: A Survey0
Cost-effective Deployment of BERT Models in Serverless Environment0
Investigating Monolingual and Multilingual BERTModels for Vietnamese Aspect Category Detection0
Distributed Deep Learning Using Volunteer Computing-Like Paradigm0
AngryBERT: Joint Learning Target and Emotion for Hate Speech Detection0
A `Sourceful' Twist: Emoji Prediction Based on Sentiment, Hashtags and Application Source0
Impact of the COVID-19 outbreak on Italy's country reputation and stock market performance: a sentiment analysis approach0
Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet ExtractionCode1
Targeted aspect based multimodal sentiment analysis:an attention capsule extraction and multi-head fusion network0
Graph Ensemble Learning over Multiple Dependency Trees for Aspect-level Sentiment Classification0
Towards Multi-Sense Cross-Lingual Alignment of Contextual EmbeddingsCode0
ASAP: A Chinese Review Dataset Towards Aspect Category Sentiment Analysis and Rating PredictionCode1
Tell Me Why You Feel That Way: Processing Compositional Dependency for Tree-LSTM Aspect Sentiment Triplet Extraction (TASTE)0
Learning to Generate Music With SentimentCode1
Improving Document-Level Sentiment Classification Using Importance of Sentences0
UnICORNN: A recurrent model for learning very long time dependenciesCode1
Sentiment Analysis for Troll Detection on Weibo0
Enhanced Aspect-Based Sentiment Analysis Models with Progressive Self-supervised Attention LearningCode1
Cycle Self-Training for Domain AdaptationCode1
Leveraging Recursive Processing for Neural-Symbolic Affect-Target Associations0
Fine-tuning Pretrained Multilingual BERT Model for Indonesian Aspect-based Sentiment Analysis0
EmoWrite: A Sentiment Analysis-Based Thought to Text Conversion -- A Validation Study0
A Novel Context-Aware Multimodal Framework for Persian Sentiment Analysis0
Video Sentiment Analysis with Bimodal Information-augmented Multi-Head Attention0
Sentiment Analysis of Users' Reviews on COVID-19 Contact Tracing Apps with a Benchmark Dataset0
A Comparison of Indonesia E-Commerce Sentiment Analysis for Marketing Intelligence Effort0
A Survey on Stance Detection for Mis- and Disinformation Identification0
COVID-19 Tweets Analysis through Transformer Language ModelsCode0
Retrieval Augmentation for Deep Neural NetworksCode0
Sentiment Analysis of Persian-English Code-mixed TextsCode0
Task-Specific Pre-Training and Cross Lingual Transfer for Code-Switched Data0
Multichannel LSTM-CNN for Telugu Technical Domain Identification0
Sentiment Analysis of Code-Mixed Social Media Text (Hinglish)0
A Novel Deep Learning Method for Textual Sentiment Analysis0
Parallelizing Legendre Memory Unit TrainingCode1
Analyzing Curriculum Learning for Sentiment Analysis along Task Difficulty, Pacing and Visualization Axes0
Sentiment Analysis for YouTube Comments in Roman Urdu0
IFoodCloud: A Platform for Real-time Sentiment Analysis of Public Opinion about Food Safety in China0
Evaluating the Performance of Some Local Optimizers for Variational Quantum Classifiers0
Decoding EEG Brain Activity for Multi-Modal Natural Language Processing0
An Effort to Measure Customer Relationship Performance in Indonesia's Fintech Industry0
An AutoML-based Approach to Multimodal Image Sentiment Analysis0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Word+ES (Scratch)Attack Success Rate100Unverified
2T5-11BAccuracy97.5Unverified
3MT-DNN-SMARTAccuracy97.5Unverified
4T5-3BAccuracy97.4Unverified
5MUPPET Roberta LargeAccuracy97.4Unverified
6StructBERTRoBERTa ensembleAccuracy97.1Unverified
7ALBERTAccuracy97.1Unverified
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