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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 551–575 of 5630 papers

Title	Date	Tasks	Status
Accuracy of a Large Language Model in Distinguishing Anti- And Pro-vaccination Messages on Social Media: The Case of Human Papillomavirus Vaccination	Apr 10, 2024	Language ModelingLanguage Modelling	—Unverified
A Panoramic Survey of Natural Language Processing in the Arab World	Nov 25, 2020	Machine TranslationOptical Character Recognition	—Unverified
A Heterogeneous Graphical Model to Understand User-Level Sentiments in Social Media	Dec 17, 2019	Opinion MiningSentiment Analysis	—Unverified
Any-gram Kernels for Sentence Classification: A Sentiment Analysis Case Study	Dec 19, 2017	General ClassificationSentence	—Unverified
A Helping Hand: Transfer Learning for Deep Sentiment Analysis	Jul 1, 2018	General ClassificationSentiment Analysis	—Unverified
Active Learning with Transfer Learning	Jul 1, 2012	Active LearningDomain Adaptation	—Unverified
OneLove beyond the field -- A few-shot pipeline for topic and sentiment analysis during the FIFA World Cup in Qatar	Aug 5, 2024	In-Context LearningSentiment Analysis	—Unverified
Assessing Sentiment Strength in Words Prior Polarities	Dec 1, 2012	Sentiment Analysis	—Unverified
An Unsupervised Multi-Document Summarization Framework Based on Neural Document Model	Dec 1, 2016	ClusteringDocument Summarization	—Unverified
``Haters gonna hate'': challenges for sentiment analysis of Facebook comments in Brazilian Portuguese	Sep 1, 2017	Sentiment Analysis	—Unverified
Active Learning Over Multiple Domains in Natural Language Tasks	Feb 1, 2022	Active LearningQuestion Answering	—Unverified
Anti-Asian Hate Speech Detection via Data Augmented Semantic Relation Inference	Apr 14, 2022	Hate Speech DetectionNatural Language Inference	—Unverified
A Novel Way of Identifying Cyber Predators	Dec 11, 2017	General ClassificationLanguage Modeling	—Unverified
Agreement and Disagreement: Comparison of Points of View in the Political Domain	Dec 1, 2016	PositionSentiment Analysis	—Unverified
Accountable Error Characterization	May 10, 2021	Sentiment Analysis	—Unverified
A Novel Twitter Sentiment Analysis Model with Baseline Correlation for Financial Market Prediction with Improved Efficiency	Mar 18, 2020	Decision MakingPrediction	—Unverified
A Novel Sentiment Analysis Engine for Preliminary Depression Status Estimation on Social Media	Nov 29, 2020	Depression DetectionSentence	—Unverified
A Graphical User Interface for Feature-Based Opinion Mining	Jun 1, 2012	Opinion MiningSentiment Analysis	—Unverified
A Novel Ensemble Deep Learning Model for Stock Prediction Based on Stock Prices and News	Jul 23, 2020	Deep LearningPhilosophy	—Unverified
AgoraSpeech: A multi-annotated comprehensive dataset of political discourse through the lens of humans and AI	Jan 9, 2025	Benchmarkingnamed-entity-recognition	—Unverified
Active Learning for Imbalanced Sentiment Classification	Jul 1, 2012	Active LearningClassification	—Unverified
Assessing Objective Recommendation Quality through Political Forecasting	Sep 1, 2017	SentenceSentiment Analysis	—Unverified
Assessing State-of-the-Art Sentiment Models on State-of-the-Art Sentiment Datasets	Sep 13, 2017	Sentiment AnalysisWord Embeddings	—Unverified
A Strategy to Combine 1stGen Transformers and Open LLMs for Automatic Text Classification	Aug 19, 2024	Sentiment Analysistext-classification	—Unverified
A Novel Deep Reinforcement Learning Based Stock Direction Prediction using Knowledge Graph and Community Aware Sentiments	Jul 2, 2021	Deep Reinforcement LearningPrediction	—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