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 2326–2350 of 5630 papers

Title	Date	Tasks	Status	Hype
Deep Learning applications for COVID-19	Jan 11, 2021	Deep LearningEpidemiology	—Unverified	0
Clustering Word Embeddings with Self-Organizing Maps. Application on LaRoSeDa -- A Large Romanian Sentiment Data Set	Jan 11, 2021	ClusteringSentiment Analysis	CodeCode Available	0
Explain and Predict, and then Predict Again	Jan 11, 2021	Explanation GenerationFact Verification	CodeCode Available	1
Learning Better Sentence Representation with Syntax Information	Jan 9, 2021	Language ModelingLanguage Modelling	—Unverified	0
Effect of Word Embedding Variable Parameters on Arabic Sentiment Analysis Performance	Jan 8, 2021	Arabic Sentiment AnalysisSentiment Analysis	—Unverified	0
BRDS: An FPGA-based LSTM Accelerator with Row-Balanced Dual-Ratio Sparsification	Jan 7, 2021	Sentiment AnalysisSentiment Classification	—Unverified	0
Mining the Relationship Between COVID-19 Sentiment and Market Performance	Jan 6, 2021	RelationSentiment Analysis	—Unverified	0
A Joint Training Dual-MRC Framework for Aspect Based Sentiment Analysis	Jan 4, 2021	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Learning Neural Networks on SVD Boosted Latent Spaces for Semantic Classification	Jan 3, 2021	General ClassificationSentiment Analysis	CodeCode Available	0
Sentiment Analysis for Open Domain Conversational Agent	Jan 3, 2021	Sentiment Analysis	—Unverified	0
Assessing Emoji Use in Modern Text Processing Tools	Jan 2, 2021	Part-Of-Speech TaggingSentiment Analysis	CodeCode Available	0
Creating Domain Dependent Turkish WordNet and SentiNet	Jan 1, 2021	LEMMASentiment Analysis	—Unverified	0
HisNet: A Polarity Lexicon based on WordNet for Emotion Analysis	Jan 1, 2021	Emotion RecognitionSentiment Analysis	—Unverified	0
On Explaining Your Explanations of BERT: An Empirical Study with Sequence Classification	Jan 1, 2021	General ClassificationSentiment Analysis	CodeCode Available	1
Learn2Weight: Weights Transfer Defense against Similar-domain Adversarial Attacks	Jan 1, 2021	Adversarial AttackDomain Adaptation	—Unverified	0
TextTN: Probabilistic Encoding of Language on Tensor Network	Jan 1, 2021	General ClassificationSentence	—Unverified	0
Meta Auxiliary Labels with Constituent-based Transformer for Aspect-based Sentiment Analysis	Jan 1, 2021	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Domain Adaptation via Anaomaly Detection	Jan 1, 2021	Anomaly DetectionDomain Adaptation	—Unverified	0
SEQUENCE-LEVEL FEATURES: HOW GRU AND LSTM CELLS CAPTURE N-GRAMS	Jan 1, 2021	Language ModelingLanguage Modelling	—Unverified	0
On the Robustness of Sentiment Analysis for Stock Price Forecasting	Jan 1, 2021	BIG-bench Machine LearningObject Recognition	—Unverified	0
Aspect-based Sentiment Classification via Reinforcement Learning	Jan 1, 2021	ClassificationGeneral Classification	—Unverified	0
Online Limited Memory Neural-Linear Bandits	Jan 1, 2021	Efficient ExplorationMulti-Armed Bandits	—Unverified	0
Feedforward Legendre Memory Unit	Jan 1, 2021	image-classificationImage Classification	—Unverified	0
Learning a Max-Margin Classifier for Cross-Domain Sentiment Analysis	Jan 1, 2021	Domain AdaptationMarketing	—Unverified	0
WordsWorth Scores for Attacking CNNs and LSTMs for Text Classification	Jan 1, 2021	ClassificationGeneral Classification	—Unverified	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