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 1251–1275 of 5630 papers

Title	Date	Tasks	Status	Score
Comprehensive dataset of user-submitted articles with ideological and extreme bias from Reddit	Aug 12, 2024	ArticlesHoldout Set	CodeCode Available	5
DIBERT: Dependency Injected Bidirectional Encoder Representations from Transformers	Dec 5, 2021	Language ModelingLanguage Modelling	CodeCode Available	5
Compressing Word Embeddings via Deep Compositional Code Learning	Nov 3, 2017	Machine TranslationQuantization	CodeCode Available	5
Aspect-based Sentiment Analysis in Question Answering Forums	Nov 1, 2021	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	5
Distilling Fine-grained Sentiment Understanding from Large Language Models	Dec 24, 2024	Sentiment AnalysisSentiment Classification	CodeCode Available	5
Enhancing Pharmacovigilance with Drug Reviews and Social Media	Apr 18, 2020	named-entity-recognitionNamed Entity Recognition	CodeCode Available	5
Aspect-based Sentiment Analysis of Scientific Reviews	Jun 5, 2020	8kActive Learning	CodeCode Available	5
Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and Documents	Nov 8, 2016	ClassificationGeneral Classification	CodeCode Available	5
Hierarchical Attention Transfer Network for Cross-Domain Sentiment Classification	Apr 26, 2018	ClassificationCross-Domain Text Classification	CodeCode Available	5
DepecheMood++: a Bilingual Emotion Lexicon Built Through Simple Yet Powerful Techniques	Oct 8, 2018	Emotion RecognitionSentiment Analysis	CodeCode Available	5
Delta-training: Simple Semi-Supervised Text Classification using Pretrained Word Embeddings	Jan 22, 2019	General ClassificationSemi-Supervised Text Classification	CodeCode Available	5
An Interpretable and Uncertainty Aware Multi-Task Framework for Multi-Aspect Sentiment Analysis	Sep 18, 2020	Extract AspectMulti-Task Learning	CodeCode Available	5
Denoising Bottleneck with Mutual Information Maximization for Video Multimodal Fusion	May 24, 2023	DenoisingMultimodal Sentiment Analysis	CodeCode Available	5
Detection of Adversarial Examples in NLP: Benchmark and Baseline via Robust Density Estimation	Nov 16, 2021	Adversarial DefenseDensity Estimation	CodeCode Available	5
Causally Denoise Word Embeddings Using Half-Sibling Regression	Nov 24, 2019	Causal Inferenceregression	CodeCode Available	5
Deep Unordered Composition Rivals Syntactic Methods for Text Classification	Jul 1, 2015	ClassificationGeneral Classification	CodeCode Available	5
Deep Pyramid Convolutional Neural Networks for Text Categorization	Jul 1, 2017	Sentiment AnalysisSentiment Classification	CodeCode Available	5
A C-LSTM Neural Network for Text Classification	Nov 27, 2015	General ClassificationSentence	CodeCode Available	5
Defense of Word-level Adversarial Attacks via Random Substitution Encoding	May 1, 2020	General ClassificationSentiment Analysis	CodeCode Available	5
Detection of Adversarial Examples in Text Classification: Benchmark and Baseline via Robust Density Estimation	May 1, 2022	Adversarial DefenseDensity Estimation	CodeCode Available	5
HPCC-YNU at SemEval-2020 Task 9: A Bilingual Vector Gating Mechanism for Sentiment Analysis of Code-Mixed Text	Oct 10, 2020	Sentiment Analysis	CodeCode Available	5
hULMonA: The Universal Language Model in Arabic	Aug 1, 2019	Arabic Sentiment AnalysisGeneral Classification	CodeCode Available	5
Deep learning for language understanding of mental health concepts derived from Cognitive Behavioural Therapy	Sep 3, 2018	Deep LearningSentence	CodeCode Available	5
Deep Learning for Hate Speech Detection in Tweets	Jun 1, 2017	16kDeep Learning	CodeCode Available	5
Deep Learning for Sentiment Analysis : A Survey	Jan 24, 2018	BIG-bench Machine LearningDeep Learning	CodeCode Available	5

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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