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 626–650 of 5630 papers

Title	Date	Tasks	Status
Attentive Gated Lexicon Reader with Contrastive Contextual Co-Attention for Sentiment Classification	Oct 1, 2018	General ClassificationOpinion Mining	—Unverified
A Two-Stage Classifier for Sentiment Analysis	Oct 1, 2013	Sentiment AnalysisText Classification	—Unverified
An Introductory Survey on Attention Mechanisms in NLP Problems	Nov 12, 2018	Dependency ParsingGeneral Classification	—Unverified
An Intelligent Data Analysis for Hotel Recommendation Systems using Machine Learning	Oct 15, 2019	BIG-bench Machine LearningCollaborative Filtering	—Unverified
An Integrated NPL Approach to Sentiment Analysis in Satisfaction Surveys	Jul 18, 2023	Opinion MiningSentiment Analysis	—Unverified
A Corpus for Dimensional Sentiment Classification on YouTube Streaming Service	Oct 1, 2021	Sentiment AnalysisSentiment Classification	—Unverified
A Transformer Based Approach towards Identification of Discourse Unit Segments and Connectives	Nov 1, 2021	Discourse ParsingDiscourse Segmentation	—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
A Case Study of Spanish Text Transformations for Twitter Sentiment Analysis	Jun 3, 2021	LemmatizationOpinion Mining	—Unverified
ATP: A holistic attention integrated approach to enhance ABSA	Aug 4, 2022	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified
An Indian Language Social Media Collection for Hate and Offensive Speech	May 1, 2020	Sentiment AnalysisSentiment Classification	—Unverified
An Improved Text Sentiment Classification Model Using TF-IDF and Next Word Negation	Jun 17, 2018	ClassificationGeneral Classification	—Unverified
A Fine-grained Interpretability Evaluation Benchmark for Neural NLP	May 23, 2022	Reading ComprehensionSentiment Analysis	—Unverified
An Improved Reinforcement Learning Model Based on Sentiment Analysis	Nov 19, 2021	reinforcement-learningReinforcement Learning	—Unverified
An Improved Approach of Intention Discovery with Machine Learning for POMDP-based Dialogue Management	Sep 20, 2020	BIG-bench Machine LearningDialogue Management	—Unverified
A Fine-Grained Annotated Corpus for Target-Based Opinion Analysis of Economic and Financial Narratives	Nov 1, 2021	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified
An Hymn of an even Deeper Sentiment Analysis	Jun 1, 2016	Common Sense ReasoningSemantic Role Labeling	—Unverified
AngryBERT: Joint Learning Target and Emotion for Hate Speech Detection	Mar 14, 2021	Hate Speech DetectionSentiment Analysis	—Unverified
Affect Proxies and Ontological Change: A finance case study	Dec 1, 2012	Sentiment Analysis	—Unverified
A Convolutional Neural Network for Aspect Sentiment Classification	Jul 4, 2018	ClassificationGeneral Classification	—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
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

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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