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 47514800 of 5630 papers

TitleStatusHype
Machine Translation Evaluation using Recurrent Neural NetworksCode0
Lingusitic Analysis of Multi-Modal Recurrent Neural Networks0
Sentiment Analysis on Monolingual, Multilingual and Code-Switching Twitter Corpora0
Negation Scope Detection for Twitter Sentiment Analysis0
Detecting speculations, contrasts and conditionals in consumer reviews0
Using Combined Lexical Resources to Identify Hashtag Types0
Optimising Agile Social Media Analysis0
A Linguistically Informed Convolutional Neural Network0
How much does word sense disambiguation help in sentiment analysis of micropost data?0
Predicting Ratings for New Movie Releases from Twitter Content0
Towards Opinion Mining from Reviews for the Prediction of Product Rankings0
Analysing domain suitability of a sentiment lexicon by identifying distributionally bipolar words0
An Exploration of Discourse-Based Sentence Spaces for Compositional Distributional Semantics0
Exploring Word Embedding for Drug Name Recognition0
Motivating Personality-aware Machine Translation0
The Rating Game: Sentiment Rating Reproducibility from Text0
Joint Prediction for Entity/Event-Level Sentiment Analysis using Probabilistic Soft Logic Models0
Adjective Intensity and Sentiment Analysis0
Closing the Gap: Domain Adaptation from Explicit to Implicit Discourse Relations0
ReVal: A Simple and Effective Machine Translation Evaluation Metric Based on Recurrent Neural NetworksCode0
Detecting Risks in the Banking System by Sentiment Analysis0
Deep Convolutional Neural Network Textual Features and Multiple Kernel Learning for Utterance-level Multimodal Sentiment Analysis0
ASTD: Arabic Sentiment Tweets DatasetCode0
PhraseRNN: Phrase Recursive Neural Network for Aspect-based Sentiment Analysis0
A quantitative analysis of gender differences in movies using psycholinguistic normatives0
Neural Networks for Open Domain Targeted SentimentCode0
Convolutional Sentence Kernel from Word Embeddings for Short Text Categorization0
Hashtag Recommendation Using Dirichlet Process Mixture Models Incorporating Types of Hashtags0
SLSA: A Sentiment Lexicon for Standard Arabic0
Cross Lingual Sentiment Analysis using Modified BRAE0
The Forest Convolutional Network: Compositional Distributional Semantics with a Neural Chart and without Binarization0
Evaluation of Word Vector Representations by Subspace AlignmentCode0
Specializing Word Embeddings for Similarity or Relatedness0
Distributed Representations for Unsupervised Semantic Role Labeling0
Towards the Extraction of Customer-to-Customer Suggestions from Reviews0
A Neural Network Model for Low-Resource Universal Dependency Parsing0
JEAM: A Novel Model for Cross-Domain Sentiment Classification Based on Emotion Analysis0
Pre-Computable Multi-Layer Neural Network Language Models0
A Multi-lingual Annotated Dataset for Aspect-Oriented Opinion Mining0
Learning Better Embeddings for Rare Words Using Distributional Representations0
Sentiment Flow - A General Model of Web Review Argumentation0
Fine-grained Opinion Mining with Recurrent Neural Networks and Word Embeddings0
Monotone Submodularity in Opinion SummariesCode0
Reinforcing the Topic of Embeddings with Theta Pure Dependence for Text Classification0
Document Modeling with Gated Recurrent Neural Network for Sentiment Classification0
Identifying Political Sentiment between Nation States with Social Media0
Squibs: Evaluation Methods for Statistically Dependent Text0
Simple Text Mining for Sentiment Analysis of Political Figure Using Naive Bayes Classifier Method0
Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment PredictionCode0
Molding CNNs for text: non-linear, non-consecutive convolutionsCode0
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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