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 5501–5550 of 5630 papers

Title	Date	Tasks	Status
Proceedings of the 2nd Workshop on Sentiment Analysis where AI meets Psychology	Dec 1, 2012	Sentiment Analysis	—Unverified
Affect Proxies and Ontological Change: A finance case study	Dec 1, 2012	Sentiment Analysis	—Unverified
Emotiphons: Emotion Markers in Conversational Speech - Comparison across Indian Languages	Dec 1, 2012	Emotion RecognitionSentiment Analysis	—Unverified
A Pilot Study of Hindustani Music Sentiments	Dec 1, 2012	Sentiment Analysis	—Unverified
Combining Social Cognitive Theories with Linguistic Features for Multi-genre Sentiment Analysis	Nov 1, 2012	Question AnsweringSentiment Analysis	—Unverified
Chinese Sentiments on the Clouds: A Preliminary Experiment on Corpus Processing and Exploration on Cloud Service	Nov 1, 2012	Opinion MiningSentiment Analysis	—Unverified
Emotional Tendency Identification for Micro-blog Topics Based on Multiple Characteristics	Nov 1, 2012	Sentiment Analysis	—Unverified
Emotion Estimation from Sentence Using Relation between Japanese Slangs and Emotion Expressions	Nov 1, 2012	Morphological AnalysisRelation	—Unverified
Annotation Scheme for Constructing Sentiment Corpus in Korean	Nov 1, 2012	Document ClassificationQuestion Answering	—Unverified
領域相關詞彙極性分析及文件情緒分類之研究 (Domain Dependent Word Polarity Analysis for Sentiment Classification) [In Chinese]	Sep 1, 2012	Sentiment AnalysisSentiment Classification	—Unverified
Unifying Local and Global Agreement and Disagreement Classification in Online Debates	Jul 1, 2012	General ClassificationSentiment Analysis	—Unverified
Prior versus Contextual Emotion of a Word in a Sentence	Jul 1, 2012	Emotion RecognitionQuestion Answering	—Unverified
Opinum: statistical sentiment analysis for opinion classification	Jul 1, 2012	ClassificationGeneral Classification	—Unverified
Sentimantics: Conceptual Spaces for Lexical Sentiment Polarity Representation with Contextuality	Jul 1, 2012	Sentiment Analysis	—Unverified
Automatically Annotating A Five-Billion-Word Corpus of Japanese Blogs for Affect and Sentiment Analysis	Jul 1, 2012	Opinion MiningSentiment Analysis	—Unverified
Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis	Jul 1, 2012	Sentiment Analysis	—Unverified
On the Impact of Sentiment and Emotion Based Features in Detecting Online Sexual Predators	Jul 1, 2012	Sentiment Analysis	—Unverified
Recognizing Arguing Subjectivity and Argument Tags	Jul 1, 2012	Semantic Textual SimilaritySentiment Analysis	—Unverified
SAMAR: A System for Subjectivity and Sentiment Analysis of Arabic Social Media	Jul 1, 2012	LemmatizationSentiment Analysis	—Unverified
POLITICAL-ADS: An annotated corpus for modeling event-level evaluativity	Jul 1, 2012	NegationSentiment Analysis	—Unverified
Who Did What to Whom? A Contrastive Study of Syntacto-Semantic Dependencies	Jul 1, 2012	Dependency ParsingMachine Translation	—Unverified
Sentiment Analysis Using a Novel Human Computation Game	Jul 1, 2012	Common Sense ReasoningGame Design	—Unverified
How do Negation and Modality Impact on Opinions?	Jul 1, 2012	Natural Language InferenceNegation	—Unverified
Multimodal Sentiment Analysis	Jul 1, 2012	Multimodal Sentiment AnalysisSentiment Analysis	—Unverified
Mining Sentiments from Tweets	Jul 1, 2012	Sentiment Analysis	—Unverified
Cross-discourse Development of Supervised Sentiment Analysis in the Clinical Domain	Jul 1, 2012	Sentiment Analysis	—Unverified
Multilingual Sentiment Analysis using Machine Translation?	Jul 1, 2012	Machine TranslationSentiment Analysis	—Unverified
Detection of Implicit Citations for Sentiment Detection	Jul 1, 2012	Sentiment Analysis	—Unverified
How to Evaluate Opinionated Keyphrase Extraction?	Jul 1, 2012	Keyphrase ExtractionMachine Translation	—Unverified
Semantic frames as an anchor representation for sentiment analysis	Jul 1, 2012	Sentiment Analysis	—Unverified
Random Walk Weighting over SentiWordNet for Sentiment Polarity Detection on Twitter	Jul 1, 2012	Sentiment Analysis	—Unverified
Analysis of Travel Review Data from Reader's Point of View	Jul 1, 2012	Sentiment Analysis	—Unverified
Subjectivity Word Sense Disambiguation	Jul 1, 2012	Sentiment AnalysisWord Sense Disambiguation	—Unverified
Multi-Domain Learning: When Do Domains Matter?	Jul 1, 2012	Domain AdaptationSentiment Analysis	—Unverified
Why Question Answering using Sentiment Analysis and Word Classes	Jul 1, 2012	Question AnsweringSentiment Analysis	—Unverified
Do Neighbours Help? An Exploration of Graph-based Algorithms for Cross-domain Sentiment Classification	Jul 1, 2012	Domain AdaptationGeneral Classification	—Unverified
Active Learning for Imbalanced Sentiment Classification	Jul 1, 2012	Active LearningClassification	—Unverified
Collocation Polarity Disambiguation Using Web-based Pseudo Contexts	Jul 1, 2012	Question AnsweringSentiment Analysis	—Unverified
Automatically Constructing a Normalisation Dictionary for Microblogs	Jul 1, 2012	Sentiment Analysis	—Unverified
UWashington: Negation Resolution using Machine Learning Methods	Jul 1, 2012	BIG-bench Machine LearningNegation	CodeCode Available
FBK: Exploiting Phrasal and Contextual Clues for Negation Scope Detection	Jul 1, 2012	NegationSentiment Analysis	—Unverified
UMichigan: A Conditional Random Field Model for Resolving the Scope of Negation	Jul 1, 2012	NegationQuestion Answering	—Unverified
*SEM 2012 Shared Task: Resolving the Scope and Focus of Negation	Jul 1, 2012	NegationSentiment Analysis	—Unverified
UCM-I: A Rule-based Syntactic Approach for Resolving the Scope of Negation	Jul 1, 2012	NegationSentiment Analysis	—Unverified
Multilingual WSD with Just a Few Lines of Code: the BabelNet API	Jul 1, 2012	Natural Language InferenceSemantic Textual Similarity	—Unverified
QuickView: NLP-based Tweet Search	Jul 1, 2012	Named Entity Recognition (NER)Semantic Role Labeling	—Unverified
Active Learning with Transfer Learning	Jul 1, 2012	Active LearningDomain Adaptation	—Unverified
Graph-based Semi-Supervised Learning Algorithms for NLP	Jul 1, 2012	Semantic ParsingSentiment Analysis	—Unverified
Multilingual Subjectivity and Sentiment Analysis	Jul 1, 2012	Sentiment Analysis	—Unverified
Identifying High-Impact Sub-Structures for Convolution Kernels in Document-level Sentiment Classification	Jul 1, 2012	General ClassificationSentiment Analysis	—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