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

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Showing 1851–1875 of 5630 papers

Title	Date	Tasks	Status
Aspect Is Not You Need: No-aspect Differential Sentiment Framework for Aspect-based Sentiment Analysis	Jul 1, 2022	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified
Evaluating Gender Bias Transfer from Film Data	Jul 1, 2022	Dialogue GenerationMachine Translation	—Unverified
Towards a Multi-Entity Aspect-Based Sentiment Analysis for Characterizing Directed Social Regard in Online Messaging	Jul 1, 2022	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified
connotation_clashers at SemEval-2022 Task 6: The effect of sentiment analysis on sarcasm detection	Jul 1, 2022	Sarcasm DetectionSentence	—Unverified
MT-Speech at SemEval-2022 Task 10: Incorporating Data Augmentation and Auxiliary Task with Cross-Lingual Pretrained Language Model for Structured Sentiment Analysis	Jul 1, 2022	Data AugmentationLanguage Modeling	—Unverified
GetSmartMSEC at SemEval-2022 Task 6: Sarcasm Detection using Contextual Word Embedding with Gaussian model for Irony Type Identification	Jul 1, 2022	Author ProfilingOpinion Mining	—Unverified
OPI at SemEval-2022 Task 10: Transformer-based Sequence Tagging with Relation Classification for Structured Sentiment Analysis	Jul 1, 2022	Relation ClassificationSentiment Analysis	CodeCode Available
UFRGSent at SemEval-2022 Task 10: Structured Sentiment Analysis using a Question Answering Model	Jul 1, 2022	PositionQuestion Answering	—Unverified
AMEX AI Labs at SemEval-2022 Task 10: Contextualized fine-tuning of BERT for Structured Sentiment Analysis	Jul 1, 2022	Sentiment Analysis	—Unverified
Response Construct Tagging: NLP-Aided Assessment for Engineering Education	Jul 1, 2022	Sentiment AnalysisSentiment Classification	—Unverified
MACSA: A Multimodal Aspect-Category Sentiment Analysis Dataset with Multimodal Fine-grained Aligned Annotations	Jun 28, 2022	Aspect Category Sentiment AnalysisSentiment Analysis	—Unverified
Adversarial Self-Attention for Language Understanding	Jun 25, 2022	Machine Reading ComprehensionNamed Entity Recognition (NER)	CodeCode Available
Sentiment Analysis with R: Natural Language Processing for Semi-Automated Assessments of Qualitative Data	Jun 25, 2022	Sentiment Analysis	—Unverified
Defending Multimodal Fusion Models against Single-Source Adversaries	Jun 25, 2022	Action Recognitionobject-detection	—Unverified
Low Resource Pipeline for Spoken Language Understanding via Weak Supervision	Jun 21, 2022	Emotion ClassificationFew-Shot Learning	—Unverified
muBoost: An Effective Method for Solving Indic Multilingual Text Classification Problem	Jun 21, 2022	Multilingual text classificationSarcasm Detection	—Unverified
Misspelling Semantics In Thai	Jun 20, 2022	Sentiment Analysis	—Unverified
Multi-scale Cooperative Multimodal Transformers for Multimodal Sentiment Analysis in Videos	Jun 16, 2022	Multimodal Sentiment AnalysisSentiment Analysis	—Unverified
CS-UM6P at SemEval-2022 Task 6: Transformer-based Models for Intended Sarcasm Detection in English and Arabic	Jun 16, 2022	Author ProfilingOpinion Mining	CodeCode Available
Label-enhanced Prototypical Network with Contrastive Learning for Multi-label Few-shot Aspect Category Detection	Jun 14, 2022	Aspect Category DetectionContrastive Learning	—Unverified
OSN Dashboard Tool For Sentiment Analysis	Jun 14, 2022	ClassificationSentiment Analysis	—Unverified
Mediators: Conversational Agents Explaining NLP Model Behavior	Jun 13, 2022	Explainable artificial intelligencemodel	—Unverified
Emoji-based Fine-grained Attention Network for Sentiment Analysis in the Microblog Comments	Jun 10, 2022	DiversitySentiment Analysis	—Unverified
Sentiment analysis on electricity twitter posts	Jun 10, 2022	Sentiment Analysis	—Unverified
Discriminative Models Can Still Outperform Generative Models in Aspect Based Sentiment Analysis	Jun 6, 2022	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified

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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