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 4976–5000 of 5630 papers

Title	Date	Tasks	Status
Ultradense Word Embeddings by Orthogonal Transformation	Feb 24, 2016	Sentiment AnalysisWord Embeddings	CodeCode Available
BERT Goes Off-Topic: Investigating the Domain Transfer Challenge using Genre Classification	Nov 27, 2023	ClassificationGenre classification	CodeCode Available
Airbnb Price Prediction Using Machine Learning and Sentiment Analysis	Jul 29, 2019	BIG-bench Machine LearningClustering	CodeCode Available
Open-Domain Targeted Sentiment Analysis via Span-Based Extraction and Classification	Jun 10, 2019	Aspect-Based Sentiment Analysis (ABSA)Aspect Term Extraction and Sentiment Classification	CodeCode Available
Word-level Textual Adversarial Attacking as Combinatorial Optimization	Oct 27, 2019	Adversarial AttackCombinatorial Optimization	CodeCode Available
Fine-grained Sentiment Classification using BERT	Oct 4, 2019	Chinese Sentiment AnalysisClassification	CodeCode Available
Fine-grained Speech Sentiment Analysis in Chinese Psychological Support Hotlines Based on Large-scale Pre-trained Model	May 7, 2024	Emotion RecognitionMulti-Label Classification	CodeCode Available
Lex2Sent: A bagging approach to unsupervised sentiment analysis	Sep 26, 2022	ClassificationDecoder	CodeCode Available
Does It Make Sense to Explain a Black Box With Another Black Box?	Apr 23, 2024	counterfactualCounterfactual Explanation	CodeCode Available
DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction	Jun 5, 2019	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available
Compositional Coding Capsule Network with K-Means Routing for Text Classification	Oct 22, 2018	ClassificationClustering	CodeCode Available
Document-level Multi-aspect Sentiment Classification by Jointly Modeling Users, Aspects, and Overall Ratings	Aug 1, 2018	General ClassificationMulti-Task Learning	CodeCode Available
BERT for Sentiment Analysis: Pre-trained and Fine-Tuned Alternatives	Jan 10, 2022	Sentiment Analysistext-classification	CodeCode Available
Aicyber at SemEval-2016 Task 4: i-vector based sentence representation	Jun 1, 2016	SentenceSentiment Analysis	CodeCode Available
Document Embedding with Paragraph Vectors	Jul 29, 2015	Document EmbeddingSentiment Analysis	CodeCode Available
openXBOW - Introducing the Passau Open-Source Crossmodal Bag-of-Words Toolkit	May 22, 2016	Document ClassificationEmotion Recognition	CodeCode Available
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
Dockerface: an Easy to Install and Use Faster R-CNN Face Detector in a Docker Container	Aug 15, 2017	Face DetectionFace Recognition	CodeCode Available
BERT-Based Sentiment Analysis: A Software Engineering Perspective	Jun 4, 2021	Recommendation SystemsSentiment Analysis	CodeCode Available
A Hybrid Approach for Aspect-Based Sentiment Analysis Using Deep Contextual Word Embeddings and Hierarchical Attention	Apr 18, 2020	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available
Fine-tuning Tree-LSTM for phrase-level sentiment classification on a Polish dependency treebank. Submission to PolEval task 2	Nov 3, 2017	General ClassificationSentiment Analysis	CodeCode Available
The MuSe 2024 Multimodal Sentiment Analysis Challenge: Social Perception and Humor Recognition	Jun 11, 2024	Humor DetectionMultimodal Sentiment Analysis	CodeCode Available
A Hybrid Approach for Aspect-Based Sentiment Analysis Using a Lexicalized Domain Ontology and Attentional Neural Models	Mar 4, 2019	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available
Lexicon-based Sentiment Analysis in German: Systematic Evaluation of Resources and Preprocessing Techniques	Sep 1, 2021	Sentiment Analysis	CodeCode Available
Advancing NLP with Cognitive Language Processing Signals	Apr 4, 2019	EEGElectroencephalogram (EEG)	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	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