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 2901–2925 of 5630 papers

Title	Date	Tasks	Status
Manovaad: A Novel Approach to Event Oriented Corpus Creation Capturing Subjectivity and Focus	May 1, 2020	ArticlesOpinion Mining	—Unverified
Comparing Machine Learning and Deep Learning Approaches on NLP Tasks for the Italian Language	May 1, 2020	BIG-bench Machine LearningClassification	—Unverified
Target-based Sentiment Annotation in Chinese Financial News	May 1, 2020	Sentiment Analysis	—Unverified
Evaluating Word Embeddings for Indonesian--English Code-Mixed Text Based on Synthetic Data	May 1, 2020	Sentiment AnalysisWord Embeddings	—Unverified
Creating a Sentiment Lexicon with Game-Specific Words for Analyzing NPC Dialogue in The Elder Scrolls V: Skyrim	May 1, 2020	Sentiment Analysis	—Unverified
Does History Matter? Using Narrative Context to Predict the Trajectory of Sentence Sentiment	May 1, 2020	SentenceSentiment Analysis	—Unverified
Affection Driven Neural Networks for Sentiment Analysis	May 1, 2020	Sentiment Analysis	—Unverified
Aspect On: an Interactive Solution for Post-Editing the Aspect Extraction based on Online Learning	May 1, 2020	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified
From Arabic Sentiment Analysis to Sarcasm Detection: The ArSarcasm Dataset	May 1, 2020	Arabic Sentiment AnalysisSarcasm Detection	—Unverified
Objective Assessment of Subjective Tasks in Crowdsourcing Applications	May 1, 2020	Sentiment Analysis	—Unverified
Odi et Amo. Creating, Evaluating and Extending Sentiment Lexicons for Latin.	May 1, 2020	Cultural Vocal Bursts Intensity PredictionSentiment Analysis	—Unverified
An Arabic Tweets Sentiment Analysis Dataset (ATSAD) using Distant Supervision and Self Training	May 1, 2020	8kArabic Sentiment Analysis	—Unverified
Offensive Language Detection Using Brown Clustering	May 1, 2020	ClusteringSentiment Analysis	—Unverified
Urban Dictionary Embeddings for Slang NLP Applications	May 1, 2020	ClusteringSarcasm Detection	—Unverified
An Annotation Framework for Luxembourgish Sentiment Analysis	May 1, 2020	ArticlesPOS	—Unverified
Email Classification Incorporating Social Networks and Thread Structure	May 1, 2020	ClassificationDocument Classification	—Unverified
Ellogon Casual Annotation Infrastructure	May 1, 2020	Sentiment Analysis	—Unverified
Optimizing Annotation Effort Using Active Learning Strategies: A Sentiment Analysis Case Study in Persian	May 1, 2020	Active LearningPersian Sentiment Analysis	—Unverified
A Term Extraction Approach to Survey Analysis in Health Care	May 1, 2020	ARCAspect-Based Sentiment Analysis	—Unverified
Towards a Multi-Dataset for Complex Emotions Learning Based on Deep Neural Networks	May 1, 2020	Sentiment AnalysisTransfer Learning	—Unverified
Information Space Dashboard	May 1, 2020	Event ExtractionSentiment Analysis	—Unverified
Metaphorical Expressions in Automatic Arabic Sentiment Analysis	May 1, 2020	Arabic Sentiment AnalysisCultural Vocal Bursts Intensity Prediction	—Unverified
Analyzing ELMo and DistilBERT on Socio-political News Classification	May 1, 2020	ClassificationGeneral Classification	—Unverified
Toward Qualitative Evaluation of Embeddings for Arabic Sentiment Analysis	May 1, 2020	Arabic Sentiment AnalysisSentiment Analysis	—Unverified
Perturbed Masking: Parameter-free Probing for Analyzing and Interpreting BERT	Apr 30, 2020	Dependency ParsingLanguage Modeling	CodeCode Available

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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	T5-11B	Accuracy	97.5	—	Unverified
3	MT-DNN-SMART	Accuracy	97.5	—	Unverified
4	T5-3B	Accuracy	97.4	—	Unverified
5	MUPPET Roberta Large	Accuracy	97.4	—	Unverified
6	StructBERTRoBERTa ensemble	Accuracy	97.1	—	Unverified
7	ALBERT	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