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.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1326–1350 of 5630 papers

Title	Date	Tasks	Status	Hype
DiaASQ : A Benchmark of Conversational Aspect-based Sentiment Quadruple Analysis	Nov 10, 2022	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	1
BERT-Based Combination of Convolutional and Recurrent Neural Network for Indonesian Sentiment Analysis	Nov 10, 2022	Deep LearningSentence	—Unverified	0
A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understanding	Nov 10, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Towards Human-Centred Explainability Benchmarks For Text Classification	Nov 10, 2022	ClassificationMisinformation	—Unverified	0
Syntax-Guided Domain Adaptation for Aspect-based Sentiment Analysis	Nov 10, 2022	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Sentiment Analysis of Persian Language: Review of Algorithms, Approaches and Datasets	Nov 9, 2022	ArticlesSentiment Analysis	—Unverified	0
Proactive Detractor Detection Framework Based on Message-Wise Sentiment Analysis Over Customer Support Interactions	Nov 8, 2022	Sentiment Analysis	—Unverified	0
AX-MABSA: A Framework for Extremely Weakly Supervised Multi-label Aspect Based Sentiment Analysis	Nov 7, 2022	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	0
AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages	Nov 7, 2022	Active LearningLanguage Modeling	CodeCode Available	1
A Multi-task Model for Sentiment Aided Stance Detection of Climate Change Tweets	Nov 7, 2022	Sentiment AnalysisStance Detection	CodeCode Available	0
Fixing Model Bugs with Natural Language Patches	Nov 7, 2022	modelRelation Extraction	CodeCode Available	1
A Comparison of Automatic Labelling Approaches for Sentiment Analysis	Nov 5, 2022	Sentiment Analysis	—Unverified	0
BERT-Deep CNN: State-of-the-Art for Sentiment Analysis of COVID-19 Tweets	Nov 4, 2022	ArticlesSentiment Analysis	—Unverified	0
A Case Study of Chinese Sentiment Analysis on Social Media Reviews Based on LSTM	Oct 31, 2022	Chinese Sentiment AnalysisSentiment Analysis	—Unverified	0
Multimodal Information Bottleneck: Learning Minimal Sufficient Unimodal and Multimodal Representations	Oct 31, 2022	Emotion RecognitionMultimodal Emotion Recognition	CodeCode Available	1
Beyond Prompting: Making Pre-trained Language Models Better Zero-shot Learners by Clustering Representations	Oct 29, 2022	ClusteringSentence	CodeCode Available	1
Sentiment Classification of Code-Switched Text using Pre-trained Multilingual Embeddings and Segmentation	Oct 29, 2022	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Improving the Modality Representation with Multi-View Contrastive Learning for Multimodal Sentiment Analysis	Oct 28, 2022	Contrastive LearningMultimodal Sentiment Analysis	—Unverified	0
On the Use of Modality-Specific Large-Scale Pre-Trained Encoders for Multimodal Sentiment Analysis	Oct 28, 2022	Multimodal Sentiment AnalysisSentiment Analysis	CodeCode Available	0
Retrieving Users' Opinions on Social Media with Multimodal Aspect-Based Sentiment Analysis	Oct 27, 2022	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	0
Exploring Robustness of Prefix Tuning in Noisy Data: A Case Study in Financial Sentiment Analysis	Oct 26, 2022	Sentiment Analysis	—Unverified	0
Leveraging Affirmative Interpretations from Negation Improves Natural Language Understanding	Oct 26, 2022	Natural Language InferenceNatural Language Understanding	CodeCode Available	0
Sinhala Sentence Embedding: A Two-Tiered Structure for Low-Resource Languages	Oct 26, 2022	SentenceSentence Embedding	—Unverified	0
Multimodal Contrastive Learning via Uni-Modal Coding and Cross-Modal Prediction for Multimodal Sentiment Analysis	Oct 26, 2022	Contrastive LearningMultimodal Sentiment Analysis	—Unverified	0
Progressive Sentiment Analysis for Code-Switched Text Data	Oct 25, 2022	Cross-Lingual Transfernamed-entity-recognition	CodeCode Available	0

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All datasets SST-2 Binary classification IMDb SST-5 Fine-grained classification Yelp Binary classification MR Yelp Fine-grained classification BanglaBook DynaSent SST-3 Sentiment Merged User and product information Amazon Review Full

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Word+ES (Scratch)	Attack Success Rate	100	—	Unverified
2	MT-DNN-SMART	Accuracy	97.5	—	Unverified
3	T5-11B	Accuracy	97.5	—	Unverified
4	MUPPET Roberta Large	Accuracy	97.4	—	Unverified
5	T5-3B	Accuracy	97.4	—	Unverified
6	ALBERT	Accuracy	97.1	—	Unverified
7	StructBERTRoBERTa ensemble	Accuracy	97.1	—	Unverified
8	XLNet (single model)	Accuracy	97	—	Unverified
9	SMARTRoBERTa	Dev Accuracy	96.9	—	Unverified
10	ELECTRA	Accuracy	96.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa-large with LlamBERT	Accuracy	96.68	—	Unverified
2	RoBERTa-large	Accuracy	96.54	—	Unverified
3	XLNet	Accuracy	96.21	—	Unverified
4	Heinsen Routing + RoBERTa Large	Accuracy	96.2	—	Unverified
5	RoBERTa-large 355M + Entailment as Few-shot Learner	Accuracy	96.1	—	Unverified
6	GraphStar	Accuracy	96	—	Unverified
7	DV-ngrams-cosine with NB sub-sampling + RoBERTa.base	Accuracy	95.94	—	Unverified
8	DV-ngrams-cosine + RoBERTa.base	Accuracy	95.92	—	Unverified
9	Roberta_Large ST + Cosine Similarity Loss	Accuracy	95.9	—	Unverified
10	BERT large finetune UDA	Accuracy	95.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Llama-3.3-70B + CAPO	Accuracy	62.27	—	Unverified
2	Mistral-Small-24B + CAPO	Accuracy	60.2	—	Unverified
3	Heinsen Routing + RoBERTa Large	Accuracy	59.8	—	Unverified
4	RoBERTa-large+Self-Explaining	Accuracy	59.1	—	Unverified
5	Qwen2.5-32B + CAPO	Accuracy	59.07	—	Unverified
6	Heinsen Routing + GPT-2	Accuracy	58.5	—	Unverified
7	BCN+Suffix BiLSTM-Tied+CoVe	Accuracy	56.2	—	Unverified
8	BERT Large	Accuracy	55.5	—	Unverified
9	LM-CPPF RoBERTa-base	Accuracy	54.9	—	Unverified
10	BCN+ELMo	Accuracy	54.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Char-level CNN	Error	4.88	—	Unverified
2	SVDCNN	Error	4.74	—	Unverified
3	LEAM	Error	4.69	—	Unverified
4	fastText, h=10, bigram	Error	4.3	—	Unverified
5	SWEM-hier	Error	4.19	—	Unverified
6	SRNN	Error	3.96	—	Unverified
7	M-ACNN	Error	3.89	—	Unverified
8	DNC+CUW	Error	3.6	—	Unverified
9	CCCapsNet	Error	3.52	—	Unverified
10	Block-sparse LSTM	Error	3.27	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Millions of Emoji	Training Time	1,500	—	Unverified
2	VLAWE	Accuracy	93.3	—	Unverified
3	RoBERTa-large 355M + Entailment as Few-shot Learner	Accuracy	92.5	—	Unverified
4	AnglE-LLaMA-7B	Accuracy	91.09	—	Unverified
5	byte mLSTM7	Accuracy	86.8	—	Unverified
6	MEAN	Accuracy	84.5	—	Unverified
7	RNN-Capsule	Accuracy	83.8	—	Unverified
8	Capsule-B	Accuracy	82.3	—	Unverified
9	SuBiLSTM-Tied	Accuracy	81.6	—	Unverified
10	USE_T+CNN	Accuracy	81.59	—	Unverified