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 876–900 of 5630 papers

Title	Date	Tasks	Status	Hype
Sentiment Analysis through LLM Negotiations	Nov 3, 2023	In-Context LearningSentiment Analysis	—Unverified	0
Joint Learning of Local and Global Features for Aspect-based Sentiment Classification	Nov 2, 2023	Graph AttentionRepresentation Learning	—Unverified	0
Is GPT Powerful Enough to Analyze the Emotions of Memes?	Nov 1, 2023	Sentiment Analysis	—Unverified	0
Learning to Play Chess from Textbooks (LEAP): a Corpus for Evaluating Chess Moves based on Sentiment Analysis	Oct 31, 2023	SentenceSentiment Analysis	CodeCode Available	0
Longer Fixations, More Computation: Gaze-Guided Recurrent Neural Networks	Oct 31, 2023	Language ModelingLanguage Modelling	—Unverified	0
Causal Interpretation of Self-Attention in Pre-Trained Transformers	Oct 31, 2023	Causal DiscoverySentiment Analysis	—Unverified	0
Non-Compositionality in Sentiment: New Data and Analyses	Oct 31, 2023	Sentiment Analysis	CodeCode Available	0
Sentiment Analysis in Digital Spaces: An Overview of Reviews	Oct 30, 2023	Sentiment Analysis	—Unverified	0
Retrofitting Light-weight Language Models for Emotions using Supervised Contrastive Learning	Oct 29, 2023	Contrastive LearningFew-Shot Learning	—Unverified	0
Atom: Low-bit Quantization for Efficient and Accurate LLM Serving	Oct 29, 2023	GPUQuantization	CodeCode Available	2
ALERTA-Net: A Temporal Distance-Aware Recurrent Networks for Stock Movement and Volatility Prediction	Oct 28, 2023	Sentiment Analysis	CodeCode Available	0
SOUL: Towards Sentiment and Opinion Understanding of Language	Oct 27, 2023	Language ModellingSentiment Analysis	CodeCode Available	0
Boosting Data Analytics With Synthetic Volume Expansion	Oct 27, 2023	Sentiment AnalysisSynthetic Data Generation	CodeCode Available	0
SentMix-3L: A Bangla-English-Hindi Code-Mixed Dataset for Sentiment Analysis	Oct 27, 2023	Sentiment Analysis	CodeCode Available	0
Large language models for aspect-based sentiment analysis	Oct 27, 2023	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	1
Understanding Social Structures from Contemporary Literary Fiction using Character Interaction Graph -- Half Century Chronology of Influential Bengali Writers	Oct 25, 2023	Information RetrievalRetrieval	—Unverified	0
BLP-2023 Task 2: Sentiment Analysis	Oct 24, 2023	Language ModelingLanguage Modelling	—Unverified	0
tagE: Enabling an Embodied Agent to Understand Human Instructions	Oct 24, 2023	DecoderNatural Language Understanding	CodeCode Available	0
Beyond Sentiment: Leveraging Topic Metrics for Political Stance Classification	Oct 24, 2023	Sentiment AnalysisStance Classification	—Unverified	0
GradSim: Gradient-Based Language Grouping for Effective Multilingual Training	Oct 23, 2023	Sentiment Analysis	—Unverified	0
Attention-Enhancing Backdoor Attacks Against BERT-based Models	Oct 23, 2023	Sentiment AnalysisTopic Classification	—Unverified	0
M2DF: Multi-grained Multi-curriculum Denoising Framework for Multimodal Aspect-based Sentiment Analysis	Oct 23, 2023	Aspect-Based Sentiment AnalysisDenoising	CodeCode Available	1
Sentiment analysis with adaptive multi-head attention in Transformer	Oct 23, 2023	DecoderSentence	—Unverified	0
MMTF-DES: A Fusion of Multimodal Transformer Models for Desire, Emotion, and Sentiment Analysis of Social Media Data	Oct 22, 2023	Emotional IntelligenceEmotion Recognition	—Unverified	0
RSM-NLP at BLP-2023 Task 2: Bangla Sentiment Analysis using Weighted and Majority Voted Fine-Tuned Transformers	Oct 22, 2023	Sentiment AnalysisTask 2	CodeCode Available	0

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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