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 14511500 of 5630 papers

TitleStatusHype
Mere Contrastive Learning for Cross-Domain Sentiment AnalysisCode1
VAuLT: Augmenting the Vision-and-Language Transformer for Sentiment Classification on Social MediaCode1
Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification0
Exploiting Unlabeled Data for Target-Oriented Opinion Words ExtractionCode1
Efficient Multimodal Transformer with Dual-Level Feature Restoration for Robust Multimodal Sentiment AnalysisCode1
LLM.int8(): 8-bit Matrix Multiplication for Transformers at ScaleCode5
Tinjauan atas Efektivitas Penggunaan Key Opinion Leader (KOL) dalam Penjualan Surat Utang Negara Ritel seri SBR011Code0
The Moral Foundations Reddit CorpusCode0
Aesthetic Visual Question Answering of Photographs0
Can Brain Signals Reveal Inner Alignment with Human Languages?Code1
DeepHider: A Covert NLP Watermarking Framework Based on Multi-task Learning0
Hybrid Multimodal Feature Extraction, Mining and Fusion for Sentiment AnalysisCode0
ATP: A holistic attention integrated approach to enhance ABSA0
PyABSA: A Modularized Framework for Reproducible Aspect-based Sentiment AnalysisCode3
ferret: a Framework for Benchmarking Explainers on TransformersCode0
Inheriting the Wisdom of Predecessors: A Multiplex Cascade Framework for Unified Aspect-based Sentiment AnalysisCode1
CubeMLP: An MLP-based Model for Multimodal Sentiment Analysis and Depression EstimationCode1
Text Classification in Memristor-based Spiking Neural NetworksCode1
Towards a Sentiment-Aware Conversational Agent0
Counterfactual Reasoning for Out-of-distribution Multimodal Sentiment AnalysisCode1
An Exploratory Study of Tweets about the SARS-CoV-2 Omicron Variant: Insights from Sentiment Analysis, Language Interpretation, Source Tracking, Type Classification, and Embedded URL Detection0
Enhancing Collaborative Filtering Recommender with Prompt-Based Sentiment AnalysisCode0
Urdu Speech and Text Based Sentiment Analyzer0
Deep Sequence Models for Text Classification Tasks0
STT: Soft Template Tuning for Few-Shot Adaptation0
Aspect-specific Context Modeling for Aspect-based Sentiment AnalysisCode1
Exploiting Word Semantics to Enrich Character Representations of Chinese Pre-trained ModelsCode0
Myers-Briggs personality classification from social media text using pre-trained language models0
SETSum: Summarization and Visualization of Student Evaluations of TeachingCode0
Sensitivity Analysis on Transferred Neural Architectures of BERT and GPT-2 for Financial Sentiment Analysis0
Multimodal Feature Extraction for Memes Sentiment Classification0
Aspect-Based Sentiment Analysis using Local Context Focus Mechanism with DeBERTa0
Deep Learning Reveals Patterns of Diverse and Changing Sentiments Towards COVID-19 Vaccines Based on 11 Million Tweets0
Predicting Out-of-Domain Generalization with Neighborhood Invariance0
A Comprehensive Review of Visual-Textual Sentiment Analysis from Social Media Networks0
Rationale-Augmented Ensembles in Language Models0
Emotion Analysis using Multi-Layered Networks for Graphical Representation of Tweets0
Detecting Islamic Radicalism Arabic Tweets Using Natural Language Processing0
Towards a Multi-Entity Aspect-Based Sentiment Analysis for Characterizing Directed Social Regard in Online Messaging0
Distantly Supervised Aspect Clustering And Naming For E-Commerce Reviews0
SPDB Innovation Lab at SemEval-2022 Task 10: A Novel End-to-End Structured Sentiment Analysis Model based on the ERNIE-M0
MT-Speech at SemEval-2022 Task 10: Incorporating Data Augmentation and Auxiliary Task with Cross-Lingual Pretrained Language Model for Structured Sentiment Analysis0
OPI at SemEval-2022 Task 10: Transformer-based Sequence Tagging with Relation Classification for Structured Sentiment AnalysisCode0
HITSZ-HLT at SemEval-2022 Task 10: A Span-Relation Extraction Framework for Structured Sentiment Analysis0
TechSSN at SemEval-2022 Task 6: Intended Sarcasm Detection using Transformer Models0
SemEval 2022 Task 10: Structured Sentiment Analysis0
UFRGSent at SemEval-2022 Task 10: Structured Sentiment Analysis using a Question Answering Model0
GetSmartMSEC at SemEval-2022 Task 6: Sarcasm Detection using Contextual Word Embedding with Gaussian model for Irony Type Identification0
CS/NLP at SemEval-2022 Task 4: Effective Data Augmentation Methods for Patronizing Language Detection and Multi-label Classification with RoBERTa and GPT30
Hitachi at SemEval-2022 Task 10: Comparing Graph- and Seq2Seq-based Models Highlights Difficulty in Structured 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