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 4201–4250 of 5630 papers

Title	Date	Tasks	Status	Hype
Tandem Anchoring: a Multiword Anchor Approach for Interactive Topic Modeling	Jul 1, 2017	Document ClassificationInformation Retrieval	—Unverified	0
Learning Cognitive Features from Gaze Data for Sentiment and Sarcasm Classification using Convolutional Neural Network	Jul 1, 2017	EEGElectroencephalogram (EEG)	—Unverified	0
Improving Distributed Representations of Tweets - Present and Future	Jun 29, 2017	Representation LearningSentiment Analysis	—Unverified	0
A Deep Neural Architecture for Sentence-level Sentiment Classification in Twitter Social Networking	Jun 25, 2017	ClassificationGeneral Classification	CodeCode Available	0
Explaining Recurrent Neural Network Predictions in Sentiment Analysis	Jun 22, 2017	General ClassificationInterpretable Machine Learning	—Unverified	0
Stance Detection in Turkish Tweets	Jun 21, 2017	Sentiment AnalysisStance Detection	—Unverified	0
How Important is Syntactic Parsing Accuracy? An Empirical Evaluation on Rule-Based Sentiment Analysis	Jun 7, 2017	Sentiment Analysis	—Unverified	0
Deep Learning for Hate Speech Detection in Tweets	Jun 1, 2017	16kDeep Learning	CodeCode Available	0
Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology Based Representations	May 31, 2017	ClassificationClustering	—Unverified	0
An Automatic Contextual Analysis and Clustering Classifiers Ensemble approach to Sentiment Analysis	May 29, 2017	ClusteringEnsemble Learning	—Unverified	0
Supervised Complementary Entity Recognition with Augmented Key-value Pairs of Knowledge	May 29, 2017	Sentiment Analysis	—Unverified	0
Contextual Explanation Networks	May 29, 2017	Image ClassificationInterpretability Techniques for Deep Learning	CodeCode Available	0
Multiple Source Domain Adaptation with Adversarial Training of Neural Networks	May 26, 2017	Domain AdaptationSentiment Analysis	CodeCode Available	0
TwiInsight: Discovering Topics and Sentiments from Social Media Datasets	May 23, 2017	Sentiment Analysis	—Unverified	0
W2VLDA: Almost Unsupervised System for Aspect Based Sentiment Analysis	May 22, 2017	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	0
Universal Dependencies Parsing for Colloquial Singaporean English	May 18, 2017	Dependency ParsingSentiment Analysis	CodeCode Available	0
On Identifying Disaster-Related Tweets: Matching-based or Learning-based?	May 4, 2017	Sentiment Analysis	CodeCode Available	0
Amobee at SemEval-2017 Task 4: Deep Learning System for Sentiment Detection on Twitter	May 3, 2017	General Classificationregression	—Unverified	0
On the effectiveness of feature set augmentation using clusters of word embeddings	May 3, 2017	ClassificationFeature Engineering	—Unverified	0
Optimizing a PoS Tagset for Norwegian Dependency Parsing	May 1, 2017	Dependency ParsingFeature Engineering	—Unverified	0
OMNIRank: Risk Quantification for P2P Platforms with Deep Learning	Apr 27, 2017	Deep LearningReading Comprehension	—Unverified	0
Decision Stream: Cultivating Deep Decision Trees	Apr 25, 2017	Classificationfeature selection	CodeCode Available	1
Learning to Skim Text	Apr 23, 2017	Document ClassificationGeneral Classification	CodeCode Available	0
BB_twtr at SemEval-2017 Task 4: Twitter Sentiment Analysis with CNNs and LSTMs	Apr 20, 2017	Sentiment AnalysisTwitter Sentiment Analysis	CodeCode Available	0
Sentiment analysis based on rhetorical structure theory: Learning deep neural networks from discourse trees	Apr 18, 2017	Data AugmentationMarketing	—Unverified	0
FEUP at SemEval-2017 Task 5: Predicting Sentiment Polarity and Intensity with Financial Word Embeddings	Apr 17, 2017	Sentiment AnalysisWord Embeddings	CodeCode Available	0
Representation Stability as a Regularizer for Improved Text Analytics Transfer Learning	Apr 12, 2017	Sentiment AnalysisTransfer Learning	—Unverified	0
What we really want to find by Sentiment Analysis: The Relationship between Computational Models and Psychological State	Apr 11, 2017	Sentiment AnalysisTransfer Learning	—Unverified	0
NILC-USP at SemEval-2017 Task 4: A Multi-view Ensemble for Twitter Sentiment Analysis	Apr 7, 2017	General ClassificationSentiment Analysis	CodeCode Available	0
An Automated Text Categorization Framework based on Hyperparameter Optimization	Apr 6, 2017	Authorship AttributionGeneral Classification	CodeCode Available	0
Learning to Generate Reviews and Discovering Sentiment	Apr 5, 2017	Sentiment AnalysisSubjectivity Analysis	CodeCode Available	0
Japanese Sentiment Classification using a Tree-Structured Long Short-Term Memory with Attention	Apr 4, 2017	ClassificationGeneral Classification	—Unverified	0
Interpretation of Semantic Tweet Representations	Apr 4, 2017	Feature EngineeringProperty Prediction	CodeCode Available	0
Aligning Entity Names with Online Aliases on Twitter	Apr 1, 2017	Coreference ResolutionEntity Linking	—Unverified	0
The Scope and Focus of Negation: A Complete Annotation Framework for Italian	Apr 1, 2017	ArticlesDecision Making	—Unverified	0
Potential and Limitations of Cross-Domain Sentiment Classification	Apr 1, 2017	ClassificationGeneral Classification	—Unverified	0
A Twitter Corpus and Benchmark Resources for German Sentiment Analysis	Apr 1, 2017	Named Entity Recognition (NER)Sentiment Analysis	—Unverified	0
Author Profiling at PAN: from Age and Gender Identification to Language Variety Identification (invited talk)	Apr 1, 2017	Author ProfilingMarketing	—Unverified	0
The BreakingNews Dataset	Apr 1, 2017	ArticlesImage Captioning	—Unverified	0
Elucidating Conceptual Properties from Word Embeddings	Apr 1, 2017	Decision MakingNamed Entity Recognition (NER)	—Unverified	0
CAT: Credibility Analysis of Arabic Content on Twitter	Apr 1, 2017	Emotion RecognitionOpinion Mining	—Unverified	0
Word Embedding and Topic Modeling Enhanced Multiple Features for Content Linking and Argument / Sentiment Labeling in Online Forums	Apr 1, 2017	ClusteringSentence	—Unverified	0
Not All Segments are Created Equal: Syntactically Motivated Sentiment Analysis in Lexical Space	Apr 1, 2017	AllClassification	—Unverified	0
Twitter Language Identification Of Similar Languages And Dialects Without Ground Truth	Apr 1, 2017	General ClassificationLanguage Identification	—Unverified	0
Word Sense Filtering Improves Embedding-Based Lexical Substitution	Apr 1, 2017	ClusteringEntity Extraction using GAN	—Unverified	0
A Code-Switching Corpus of Turkish-German Conversations	Apr 1, 2017	Automatic Speech Recognition (ASR)Language Identification	—Unverified	0
A Characterization Study of Arabic Twitter Data with a Benchmarking for State-of-the-Art Opinion Mining Models	Apr 1, 2017	BenchmarkingFeature Engineering	—Unverified	0
Sentiment Analysis and Lexical Cohesion for the Story Cloze Task	Apr 1, 2017	Sentiment Analysis	—Unverified	0
Debunking Sentiment Lexicons: A Case of Domain-Specific Sentiment Classification for Croatian	Apr 1, 2017	ClassificationGeneral Classification	—Unverified	0
Comparison of Short-Text Sentiment Analysis Methods for Croatian	Apr 1, 2017	General ClassificationSentiment Analysis	—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