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 50015050 of 5630 papers

TitleStatusHype
An Analysis of Radicals-based Features in Subjectivity Classification on Simplified Chinese Sentences0
Determing Trustworthiness in E-Commerce Customer Reviews0
Word-level Language Identification in Bi-lingual Code-switched Texts0
Automatically Building a Corpus for Sentiment Analysis on Indonesian Tweets0
Effective Use of Word Order for Text Categorization with Convolutional Neural NetworksCode0
Merging Verb Senses of Hindi WordNet using Word Embeddings0
LABR: A Large Scale Arabic Sentiment Analysis BenchmarkCode0
Visual Sentiment Prediction with Deep Convolutional Neural Networks0
The Effect of Temporal-based Term Selection for Text Classification0
Sentiment Analysis based on User Tag for Traditional Chinese Medicine in Weibo0
Polarization Measurement of High Dimensional Social Media Messages With Support Vector Machine Algorithm Using Mapreduce0
A Scalable, Lexicon Based Technique for Sentiment Analysis0
Corpora Preparation and Stopword List Generation for Arabic data in Social Network0
A Sentiment-aligned Topic Model for Product Aspect Rating Prediction0
Predicting Attrition Along the Way: The UIUC Model0
Financial Keyword Expansion via Continuous Word Vector Representations0
Abstractive Summarization of Product Reviews Using Discourse Structure0
Learning from a Neighbor: Adapting a Japanese Parser for Korean Through Feature Transfer Learning0
Exploiting Social Relations and Sentiment for Stock Prediction0
Sentiment Analysis on the People's Daily0
Aligning context-based statistical models of language with brain activity during reading0
Evaluating Distant Supervision for Subjectivity and Sentiment Analysis on Arabic Twitter Feeds0
Fine-Grained Contextual Predictions for Hard Sentiment Words0
A Joint Segmentation and Classification Framework for Sentiment Analysis0
Learning Emotion Indicators from Tweets: Hashtags, Hashtag Patterns, and Phrases0
Explaining the Stars: Weighted Multiple-Instance Learning for Aspect-Based Sentiment Analysis0
Event Role Extraction using Domain-Relevant Word Representations0
Clustering Aspect-related Phrases by Leveraging Sentiment Distribution Consistency0
A Dependency Parser for Tweets0
The Inside-Outside Recursive Neural Network model for Dependency Parsing0
A Supervised Approach for Sentiment Analysis using Skipgrams0
A Neural Network for Factoid Question Answering over Paragraphs0
Positive Unlabeled Learning for Deceptive Reviews Detection0
A Large Scale Arabic Sentiment Lexicon for Arabic Opinion Mining0
Foreign Words and the Automatic Processing of Arabic Social Media Text Written in Roman Script0
+/-EffectWordNet: Sense-level Lexicon Acquisition for Opinion Inference0
Polarity detection movie reviews in hindi language0
Exploiting Social Network Structure for Person-to-Person Sentiment Analysis0
Feature-Frequency--Adaptive On-line Training for Fast and Accurate Natural Language Processing0
Think Positive: Towards Twitter Sentiment Analysis from Scratch0
TJP: Identifying the Polarity of Tweets from Contexts0
ECNU: A Combination Method and Multiple Features for Aspect Extraction and Sentiment Polarity Classification0
Multi-Lingual Sentiment Analysis of Social Data Based on Emotion-Bearing Patterns0
Common Space Embedding of Primal-Dual Relation Semantic Spaces0
A broad-coverage collection of portable NLP components for building shareable analysis pipelines0
SINAI: Voting System for Aspect Based Sentiment Analysis0
SINAI: Voting System for Twitter Sentiment Analysis0
COMMIT-P1WP3: A Co-occurrence Based Approach to Aspect-Level Sentiment Analysis0
A Rule-Based Approach to Aspect Extraction from Product Reviews0
SentiKLUE: Updating a Polarity Classifier in 48 Hours0
Show:102550
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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