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 1701–1725 of 5630 papers

Title	Date	Tasks	Status
Balotage in Argentina 2015, a sentiment analysis of tweets	Nov 7, 2016	Sentiment Analysis	—Unverified
Ballpark Learning: Estimating Labels from Rough Group Comparisons	Jun 30, 2016	Sentiment Analysis	—Unverified
An Eye-tracking Study of Named Entity Annotation	Sep 1, 2017	Active LearningCoreference Resolution	—Unverified
Affective Common Sense Knowledge Acquisition for Sentiment Analysis	May 1, 2012	Common Sense ReasoningDecision Making	—Unverified
Balancing Translation Quality and Sentiment Preservation (Non-archival Extended Abstract)	Mar 1, 2018	Sentiment AnalysisTranslation	—Unverified
Balancing Innovation and Privacy: Data Security Strategies in Natural Language Processing Applications	Oct 11, 2024	Computational EfficiencyMachine Translation	—Unverified
Balancing Between Over-Weighting and Under-Weighting in Supervised Term Weighting	Apr 14, 2016	Sentiment AnalysisSentiment Classification	—Unverified
An Exploratory Study of Tweets about the SARS-CoV-2 Omicron Variant: Insights from Sentiment Analysis, Language Interpretation, Source Tracking, Type Classification, and Embedded URL Detection	Jul 20, 2022	Sentiment Analysis	—Unverified
Affection Driven Neural Networks for Sentiment Analysis	May 1, 2020	Sentiment Analysis	—Unverified
A Case Study of Machine Translation in Financial Sentiment Analysis	Sep 1, 2017	Machine TranslationSentiment Analysis	—Unverified
Efficient Solutions For An Intriguing Failure of LLMs: Long Context Window Does Not Mean LLMs Can Analyze Long Sequences Flawlessly	Aug 3, 2024	Sentiment Analysis	—Unverified
Bag of Tricks for Effective Language Model Pretraining and Downstream Adaptation: A Case Study on GLUE	Feb 18, 2023	Contrastive LearningDenoising	—Unverified
An Exploration of Discourse-Based Sentence Spaces for Compositional Distributional Semantics	Sep 1, 2015	Machine TranslationNatural Language Inference	—Unverified
BadNL: Backdoor Attacks Against NLP Models	Jun 18, 2021	Backdoor AttackSentence	—Unverified
BACN: Bi-direction Attention Capsule-based Network for Multimodal Sentiment Analysis	Nov 16, 2021	Multimodal Sentiment AnalysisSentiment Analysis	—Unverified
An Experiment in Integrating Sentiment Features for Tech Stock Prediction in Twitter	Dec 1, 2012	Named Entity Recognition (NER)Sentiment Analysis	—Unverified
Affect in Tweets Using Experts Model	Mar 20, 2019	Mixture-of-Expertsmodel	—Unverified
Domain Adaptation with Category Attention Network for Deep Sentiment Analysis	Dec 31, 2021	AttributeClassification	—Unverified
DOMAIN ADAPTATION VIA DISTRIBUTION AND REPRESENTATION MATCHING: A CASE STUDY ON TRAINING DATA SELECTION VIA REINFORCEMENT LEARNING	Sep 27, 2018	Dependency ParsingDomain Adaptation	—Unverified
Domain Adaptation via Anaomaly Detection	Jan 1, 2021	Anomaly DetectionDomain Adaptation	—Unverified
Domain Adaptation Using a Combination of Multiple Embeddings for Sentiment Analysis	Dec 1, 2018	Domain AdaptationSentiment Analysis	—Unverified
Domain Adaptation of Transformer-Based Models using Unlabeled Data for Relevance and Polarity Classification of German Customer Feedback	Dec 12, 2022	ClassificationDomain Adaptation	—Unverified
Domain Aggregation Networks for Multi-Source Domain Adaptation	Sep 11, 2019	Domain AdaptationSentiment Analysis	—Unverified
Domain and Task-Informed Sample Selection for Cross-Domain Target-based Sentiment Analysis	Nov 1, 2021	Sentiment Analysis	—Unverified
BabelDomains: Large-Scale Domain Labeling of Lexical Resources	Apr 1, 2017	ClusteringDomain Adaptation	—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