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 44014450 of 5630 papers

TitleStatusHype
Convolutional Neural Network Language ModelsCode0
Learning Term Embeddings for Taxonomic Relation Identification Using Dynamic Weighting Neural Network0
Neural Sentiment Classification with User and Product AttentionCode0
Context-Sensitive Lexicon Features for Neural Sentiment AnalysisCode0
Does `well-being' translate on Twitter?0
Automatic Extraction of Implicit Interpretations from Modal Constructions0
Robust Gram EmbeddingsCode0
Extracting Aspect Specific Opinion Expressions0
Real-Time Speech Emotion and Sentiment Recognition for Interactive Dialogue Systems0
Lifelong-RL: Lifelong Relaxation Labeling for Separating Entities and Aspects in Opinion Targets0
Improving Twitter Sentiment Classification via Multi-Level Sentiment-Enriched Word Embeddings0
Mining Social Media for Open Innovation in Transportation Systems0
Sentiment Analysis of Review Datasets Using Naive Bayes and K-NN Classifier0
Sentiment Analysis of Twitter Data for Predicting Stock Market MovementsCode1
A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural NetworksCode0
Lexicon Integrated CNN Models with Attention for Sentiment Analysis0
Cached Long Short-Term Memory Neural Networks for Document-Level Sentiment Classification0
SentiHood: Targeted Aspect Based Sentiment Analysis Dataset for Urban Neighbourhoods0
Supervised Term Weighting Metrics for Sentiment Analysis in Short Text0
Correlation-Based Method for Sentiment Classification0
Neural Structural Correspondence Learning for Domain AdaptationCode0
Sentiment Analysis on Bangla and Romanized Bangla Text (BRBT) using Deep Recurrent models0
Sarcasm Detection in Chinese Using a Crowdsourced Corpus0
Computing Sentiment Scores of Verb Phrases for Vietnamese0
Event Based Emotion Classification for News Articles0
Sentiment Clustering with Topic and Temporal Information from Large Email Dataset0
emoji2vec: Learning Emoji Representations from their DescriptionCode0
Twitter Opinion Topic Model: Extracting Product Opinions from Tweets by Leveraging Hashtags and Sentiment Lexicon0
Select-Additive Learning: Improving Generalization in Multimodal Sentiment AnalysisCode0
A Hierarchical Model of Reviews for Aspect-based Sentiment Analysis0
INSIGHT-1 at SemEval-2016 Task 4: Convolutional Neural Networks for Sentiment Classification and Quantification0
INSIGHT-1 at SemEval-2016 Task 5: Deep Learning for Multilingual Aspect-based Sentiment Analysis0
Sentiment Classification of Food Reviews0
Sarcastic Soulmates: Intimacy and irony markers in social media messaging0
Evaluative Pattern Extraction for Automated Text Generation0
Automatic Generation of Student Report Cards0
Book Review: Sentiment Analysis: Mining Opinions, Sentiments, and Emotions by Bing Liu0
Dynamic Allocation of Crowd Contributions for Sentiment Analysis during the 2016 U.S. Presidential Election0
Applying Naive Bayes Classification to Google Play Apps Categorization0
Semantic descriptions of 24 evaluational adjectives, for application in sentiment analysis0
SlangSD: Building and Using a Sentiment Dictionary of Slang Words for Short-Text Sentiment Classification0
``What Is Your Evidence?'' A Study of Controversial Topics on Social Media0
How to Train good Word Embeddings for Biomedical NLPCode0
Intrinsic Evaluation of Word Vectors Fails to Predict Extrinsic Performance0
Sentence Embedding Evaluation Using Pyramid Annotation0
Scrutable Feature Sets for Stance Classification0
Neural Attention Model for Classification of Sentences that Support Promoting/Suppressing Relationship0
Parameterized context windows in Random Indexing0
Learning Word Importance with the Neural Bag-of-Words ModelCode0
Leveraging Annotators' Gaze Behaviour for Coreference Resolution0
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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