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 19011950 of 5630 papers

TitleStatusHype
Pay attention to emoji: Feature Fusion Network with EmoGraph2vec Model for Sentiment Analysis0
Emoji-based Co-attention Network for Microblog Sentiment Analysis0
Adversarial Attacks and Defenses for Social Network Text Processing Applications: Techniques, Challenges and Future Research Directions0
Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment AnalysisCode1
DASentimental: Detecting depression, anxiety and stress in texts via emotional recall, cognitive networks and machine learning0
Generating artificial texts as substitution or complement of training data0
Hate and Offensive Speech Detection in Hindi and Marathi0
ClimateBert: A Pretrained Language Model for Climate-Related TextCode1
Adverse Media Mining for KYC and ESG Compliance0
Improved Multilingual Language Model Pretraining for Social Media Text via Translation Pair PredictionCode0
Distributionally Robust Classifiers in Sentiment AnalysisCode0
The R package sentometrics to compute, aggregate and predict with textual sentiment0
SentimentArcs: A Novel Method for Self-Supervised Sentiment Analysis of Time Series Shows SOTA Transformers Can Struggle Finding Narrative ArcsCode1
Fine-Grained Opinion Summarization with Minimal Supervision0
On the current state of reproducibility and reporting of uncertainty for Aspect-based Sentiment Analysis0
n-stage Latent Dirichlet Allocation: A Novel Approach for LDACode0
Span Detection for Aspect-Based Sentiment Analysis in VietnameseCode1
RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP ModelsCode1
StreaMulT: Streaming Multimodal Transformer for Heterogeneous and Arbitrary Long Sequential Data0
Solving Aspect Category Sentiment Analysis as a Text Generation TaskCode1
Aspect-Sentiment-Multiple-Opinion Triplet ExtractionCode0
Practical Benefits of Feature Feedback Under Distribution Shift0
The Dawn of Quantum Natural Language ProcessingCode1
Topic Modeling, Clade-assisted Sentiment Analysis, and Vaccine Brand Reputation Analysis of COVID-19 Vaccine-related Facebook Comments in the PhilippinesCode0
Calling to CNN-LSTM for Rumor Detection: A Deep Multi-channel Model for Message Veracity Classification in Microblogs0
Sentiment Analysis and Topic Modeling for COVID-19 Vaccine Discussions0
Unsupervised Multimodal Language Representations using Convolutional Autoencoders0
KNOT: Knowledge Distillation using Optimal Transport for Solving NLP TasksCode1
Exploring Conditional Text Generation for Aspect-Based Sentiment AnalysisCode0
Using Psuedolabels for training Sentiment Classifiers makes the model generalize better across datasets0
Privacy enabled Financial Text Classification using Differential Privacy and Federated Learning0
Relation Analysis between Hotel Review Rating Scores and Sentiment Analysis of Reviews by Chinese Tourists Visiting Japan0
Aspect Sentiment Quad Prediction as Paraphrase GenerationCode1
A Comparative Study of Sentiment Analysis Using NLP and Different Machine Learning Techniques on US Airline Twitter Data0
Aggregating User-Centric and Post-Centric Sentiments from Social Media for Topical Stance Prediction0
NCU-NLP at ROCLING-2021 Shared Task: Using MacBERT Transformers for Dimensional Sentiment Analysis0
SCUDS at ROCLING-2021 Shared Task: Using Pretrained Model for Dimensional Sentiment Analysis Based on Sample Expansion Method0
ntust-nlp-1 at ROCLING-2021 Shared Task: Educational Texts Dimensional Sentiment Analysis using Pretrained Language Models0
A Corpus for Dimensional Sentiment Classification on YouTube Streaming Service0
What confuses BERT? Linguistic Evaluation of Sentiment Analysis on Telecom Customer Opinion0
Using Valence and Arousal-infused Bi-LSTM for Sentiment Analysis in Social Media Product Reviews0
CYUT at ROCLING-2021 Shared Task: Based on BERT and MacBERT0
Home Appliance Review Research Via Adversarial Reptile0
Aspect-Based Sentiment Analysis and Singer Name Entity Recognition using Parameter Generation Network Based Transfer Learning0
SoochowDS at ROCLING-2021 Shared Task: Text Sentiment Analysis Using BERT and LSTM0
MMTL: The Meta Multi-Task Learning for Aspect Category Sentiment Analysis0
ROCLING-2021 Shared Task: Dimensional Sentiment Analysis for Educational Texts0
ntust-nlp-2 at ROCLING-2021 Shared Task: BERT-based semantic analyzer with word-level information0
BERT4GCN: Using BERT Intermediate Layers to Augment GCN for Aspect-based Sentiment Classification0
UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis0
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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