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 35013550 of 5630 papers

TitleStatusHype
Paraphrase Thought: Sentence Embedding Module Imitating Human Language RecognitionCode0
SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis0
Exploiting Deep Learning for Persian Sentiment Analysis0
Multimodal Language Analysis with Recurrent Multistage FusionCode0
Building a Kannada POS Tagger Using Machine Learning and Neural Network ModelsCode0
Sentimental Content Analysis and Knowledge Extraction from News Articles0
Code-Mixed Sentiment Analysis Using Machine Learning and Neural Network Approaches0
A Survey on Sentiment and Emotion Analysis for Computational Literary Studies0
Exploiting Effective Representations for Chinese Sentiment Analysis Using a Multi-Channel Convolutional Neural Network0
A Multi-task Ensemble Framework for Emotion, Sentiment and Intensity Prediction0
Transfer Learning for Entity Recognition of Novel ClassesCode0
Model-Free Context-Aware Word Composition0
Distinguishing affixoid formations from compoundsCode0
JeSemE: Interleaving Semantics and Emotions in a Web Service for the Exploration of Language Change Phenomena0
Automatically Creating a Lexicon of Verbal Polarity Shifters: Mono- and Cross-lingual Methods for GermanCode0
Adaptive Learning of Local Semantic and Global Structure Representations for Text Classification0
Simple Algorithms For Sentiment Analysis On Sentiment Rich, Data Poor Domains.0
NLP for Conversations: Sentiment, Summarization, and Group Dynamics0
Learning Semantic Sentence Embeddings using Sequential Pair-wise DiscriminatorCode0
Expressively vulgar: The socio-dynamics of vulgarity and its effects on sentiment analysis in social mediaCode0
Deep Bayesian Learning and Understanding0
Using J-K-fold Cross Validation To Reduce Variance When Tuning NLP ModelsCode0
Hybrid Attention based Multimodal Network for Spoken Language Classification0
Incorporating Deep Visual Features into Multiobjective based Multi-view Search Results Clustering0
Task-oriented Word Embedding for Text ClassificationCode0
Learning Sentiment Composition from Sentiment Lexicons0
Aspect-based summarization of pros and cons in unstructured product reviewsCode0
Representations and Architectures in Neural Sentiment Analysis for Morphologically Rich Languages: A Case Study from Modern Hebrew0
Document-level Multi-aspect Sentiment Classification by Jointly Modeling Users, Aspects, and Overall RatingsCode0
RuSentiment: An Enriched Sentiment Analysis Dataset for Social Media in Russian0
Enhancing General Sentiment Lexicons for Domain-Specific Use0
Learning Word Meta-Embeddings by AutoencodingCode0
Twitter corpus of Resource-Scarce Languages for Sentiment Analysis and Multilingual Emoji Prediction0
Fine-Grained Arabic Dialect Identification0
A Knowledge-Augmented Neural Network Model for Implicit Discourse Relation Classification0
Enhanced Aspect Level Sentiment Classification with Auxiliary Memory0
Projecting Embeddings for Domain Adaption: Joint Modeling of Sentiment Analysis in Diverse DomainsCode0
Effective Attention Modeling for Aspect-Level Sentiment Classification0
A review of Spanish corpora annotated with negationCode0
A Lexicon-Based Supervised Attention Model for Neural Sentiment Analysis0
Aspect and Sentiment Aware Abstractive Review Summarization0
Encoding Sentiment Information into Word Vectors for Sentiment Analysis0
Towards Coreference for Literary Text: Analyzing Domain-Specific Phenomena0
An Evaluation of Lexicon-based Sentiment Analysis Techniques for the Plays of Gotthold Ephraim Lessing0
The Other Side of the Coin: Unsupervised Disambiguation of Potentially Idiomatic Expressions by Contrasting Senses0
YouTube AV 50K: An Annotated Corpus for Comments in Autonomous VehiclesCode0
Learning low dimensional word based linear classifiers using Data Shared Adaptive Bootstrap Aggregated Lasso with application to IMDb data0
Text Classification based on Multiple Block Convolutional Highways0
Twitter Sentiment Analysis via Bi-sense Emoji Embedding and Attention-based LSTM0
Twitter Sentiment Analysis System0
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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