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 851900 of 5630 papers

TitleStatusHype
SBTRec- A Transformer Framework for Personalized Tour Recommendation Problem with Sentiment Analysis0
Improving Unimodal Inference with Multimodal Transformers0
A Systematic Review of Aspect-based Sentiment Analysis: Domains, Methods, and Trends0
A BERT based Ensemble Approach for Sentiment Classification of Customer Reviews and its Application to Nudge Marketing in e-Commerce0
A Comparative Analysis of the COVID-19 Infodemic in English and Chinese: Insights from Social Media Textual Data0
How good are Large Language Models on African Languages?0
BIDRN: A Method of Bidirectional Recurrent Neural Network for Sentiment Analysis0
GPT-4V(ision) as A Social Media Analysis Engine0
GIELLM: Japanese General Information Extraction Large Language Model Utilizing Mutual Reinforcement Effect0
Zero-Shot Cross-Lingual Sentiment Classification under Distribution Shift: an Exploratory Study0
CompCodeVet: A Compiler-guided Validation and Enhancement Approach for Code Dataset0
LLMs Learn Task Heuristics from Demonstrations: A Heuristic-Driven Prompting Strategy for Document-Level Event Argument ExtractionCode1
A Comparison of Lexicon-Based and ML-Based Sentiment Analysis: Are There Outlier Words?0
Mental Health Diagnosis in the Digital Age: Harnessing Sentiment Analysis on Social Media Platforms upon Ultra-Sparse Feature Content0
Deep Learning Brasil at ABSAPT 2022: Portuguese Transformer Ensemble ApproachesCode0
RankAug: Augmented data ranking for text classification0
RDGCN: Reinforced Dependency Graph Convolutional Network for Aspect-based Sentiment AnalysisCode1
Twitter Sentiment Analysis of Covid Vacciness0
Modelling Sentiment Analysis: LLMs and data augmentation techniquesCode0
iACOS: Advancing Implicit Sentiment Extraction with Informative and Adaptive Negative ExamplesCode0
mahaNLP: A Marathi Natural Language Processing Library0
Enhancing search engine precision and user experience through sentiment-based polysemy resolution0
An Empirical Study of Benchmarking Chinese Aspect Sentiment Quad Prediction0
Indo LEGO-ABSA: A Multitask Generative Aspect Based Sentiment Analysis for Indonesian LanguageCode0
Data-Free Distillation of Language Model by Text-to-Text Transfer0
Sentiment Analysis through LLM Negotiations0
Joint Learning of Local and Global Features for Aspect-based Sentiment Classification0
Is GPT Powerful Enough to Analyze the Emotions of Memes?0
Learning to Play Chess from Textbooks (LEAP): a Corpus for Evaluating Chess Moves based on Sentiment AnalysisCode0
Longer Fixations, More Computation: Gaze-Guided Recurrent Neural Networks0
Causal Interpretation of Self-Attention in Pre-Trained Transformers0
Non-Compositionality in Sentiment: New Data and AnalysesCode0
Sentiment Analysis in Digital Spaces: An Overview of Reviews0
Retrofitting Light-weight Language Models for Emotions using Supervised Contrastive Learning0
Atom: Low-bit Quantization for Efficient and Accurate LLM ServingCode2
ALERTA-Net: A Temporal Distance-Aware Recurrent Networks for Stock Movement and Volatility PredictionCode0
SOUL: Towards Sentiment and Opinion Understanding of LanguageCode0
Boosting Data Analytics With Synthetic Volume ExpansionCode0
SentMix-3L: A Bangla-English-Hindi Code-Mixed Dataset for Sentiment AnalysisCode0
Large language models for aspect-based sentiment analysisCode1
Understanding Social Structures from Contemporary Literary Fiction using Character Interaction Graph -- Half Century Chronology of Influential Bengali Writers0
BLP-2023 Task 2: Sentiment Analysis0
tagE: Enabling an Embodied Agent to Understand Human InstructionsCode0
Beyond Sentiment: Leveraging Topic Metrics for Political Stance Classification0
GradSim: Gradient-Based Language Grouping for Effective Multilingual Training0
Attention-Enhancing Backdoor Attacks Against BERT-based Models0
M2DF: Multi-grained Multi-curriculum Denoising Framework for Multimodal Aspect-based Sentiment AnalysisCode1
Sentiment analysis with adaptive multi-head attention in Transformer0
MMTF-DES: A Fusion of Multimodal Transformer Models for Desire, Emotion, and Sentiment Analysis of Social Media Data0
RSM-NLP at BLP-2023 Task 2: Bangla Sentiment Analysis using Weighted and Majority Voted Fine-Tuned TransformersCode0
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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