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 34013450 of 5630 papers

TitleStatusHype
Self-Attention: A Better Building Block for Sentiment Analysis Neural Network ClassifiersCode0
Towards Deep Conversational RecommendationsCode0
TextBugger: Generating Adversarial Text Against Real-world ApplicationsCode0
Code Failure Prediction and Pattern Extraction using LSTM Networks0
Predicting the Effects of News Sentiments on the Stock MarketCode0
An Unsupervised Approach for Aspect Category Detection Using Soft Cosine Similarity MeasureCode0
Leveraging Multi-grained Sentiment Lexicon Information for Neural Sequence Models0
Practical Text Classification With Large Pre-Trained Language ModelsCode0
Domain Adaptation for Sentiment Analysis using Keywords in the Target Domain as the Learning Weight0
GLoMo: Unsupervised Learning of Transferable Relational Graphs0
We Usually Don't Like Going to the Dentist: Using Common Sense to Detect Irony on Twitter0
Domain Adaptation Using a Combination of Multiple Embeddings for Sentiment Analysis0
Adversarial Multiple Source Domain Adaptation0
Food-Related Sentiment Analysis for Cantonese0
Modality-based Factorization for Multimodal Fusion0
EvoMSA: A Multilingual Evolutionary Approach for Sentiment AnalysisCode0
GIRNet: Interleaved Multi-Task Recurrent State Sequence ModelsCode0
Movie Recommendation System using Sentiment Analysis from Microblogging DataCode0
SOC: hunting the underground inside story of the ethereum Social-network Opinion and Comment0
Sentiment Analysis of Financial News Articles using Performance Indicators0
Recurrently Controlled Recurrent NetworksCode0
Explicit Interaction Model towards Text ClassificationCode0
Words Can Shift: Dynamically Adjusting Word Representations Using Nonverbal BehaviorsCode0
Learning Robust Heterogeneous Signal Features from Parallel Neural Network for Audio Sentiment Analysis0
Quantifying Uncertainties in Natural Language Processing Tasks0
Deep Discriminative Learning for Unsupervised Domain Adaptation0
Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment ClassificationCode0
A Self-Attentive Hierarchical Model for Jointly Improving Text Summarization and Sentiment Classification0
An Introductory Survey on Attention Mechanisms in NLP Problems0
Long Short-Term Memory with Dynamic Skip ConnectionsCode0
Importance of Self-Attention for Sentiment Analysis0
Cyclegen: Cyclic consistency based product review generator from attributes0
DERE: A Task and Domain-Independent Slot Filling Framework for Declarative Relation Extraction0
Distantly Supervised Attribute Detection from Reviews0
When does deep multi-task learning work for loosely related document classification tasks?0
Helping each Other: A Framework for Customer-to-Customer Suggestion Mining using a Semi-supervised Deep Neural Network0
SyntaViz: Visualizing Voice Queries through a Syntax-Driven Hierarchical OntologyCode0
Recurrent Attention Unit0
Topic-Specific Sentiment Analysis Can Help Identify Political Ideology0
Variational Semi-supervised Aspect-term Sentiment Analysis via Transformer0
Compositional Coding Capsule Network with K-Means Routing for Text ClassificationCode0
On Zero-shot Cross-lingual Transfer of Multilingual Neural Machine Translation0
Learning Robust Joint Representations for Multimodal Sentiment Analysis0
Cross-domain aspect extraction for sentiment analysis: a transductive learning approach0
Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New ExperimentsCode0
Packaging and Sharing Machine Learning Models via the Acumos AI Open Platform0
Super Characters: A Conversion from Sentiment Classification to Image Classification0
Towards a One-stop Solution to Both Aspect Extraction and Sentiment Analysis Tasks with Neural Multi-task Learning0
DepecheMood++: a Bilingual Emotion Lexicon Built Through Simple Yet Powerful TechniquesCode0
Text-based Sentiment Analysis and Music Emotion Recognition0
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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