Papers Sentiment Classification
“Sentiment Classification” 태그가 달린 논문 949편 · 필터 해제
Unimodal Intermediate Training for Multimodal Meme Sentiment Classification
Internet Memes remain a challenging form of user-generated content for automated sentiment classification. The availability of labelled memes is a barrier to developing sentiment classifiers of multimodal memes. To addre…
ClassificationSentiment AnalysisSentiment ClassificationA Dataset and Strong Baselines for Classification of Czech News Texts
Pre-trained models for Czech Natural Language Processing are often evaluated on purely linguistic tasks (POS tagging, parsing, NER) and relatively simple classification tasks such as sentiment classification or article c…
ArticlesClassificationNERNews Classification+4Is Prompt-Based Finetuning Always Better than Vanilla Finetuning? Insights from Cross-Lingual Language Understanding
Multilingual pretrained language models (MPLMs) have demonstrated substantial performance improvements in zero-shot cross-lingual transfer across various natural language understanding tasks by finetuning MPLMs on task-s…
Cross-Lingual TransferNatural Language InferenceNatural Language UnderstandingParaphrase Identification+3Convolutional Neural Networks for Sentiment Analysis on Weibo Data: A Natural Language Processing Approach
This study addressed the complex task of sentiment analysis on a dataset of 119,988 original tweets from Weibo using a Convolutional Neural Network (CNN), offering a new approach to Natural Language Processing (NLP). The…
Sentiment AnalysisSentiment ClassificationWord EmbeddingsBetter Handling Coreference Resolution in Aspect Level Sentiment Classification by Fine-Tuning Language Models
Customer feedback is invaluable to companies as they refine their products. Monitoring customer feedback can be automated with Aspect Level Sentiment Classification (ALSC) which allows us to analyse specific aspects of t…
coreference-resolutionCoreference ResolutionSentiment AnalysisSentiment ClassificationIs ChatGPT a Good Personality Recognizer? A Preliminary Study
In recent years, personality has been regarded as a valuable personal factor being incorporated into numerous tasks such as sentiment analysis and product recommendation. This has led to widespread attention to text-base…
FairnessLogical ReasoningProduct RecommendationSentiment Analysis+1Constructing Colloquial Dataset for Persian Sentiment Analysis of Social Microblogs
Introduction: Microblogging websites have massed rich data sources for sentiment analysis and opinion mining. In this regard, sentiment classification has frequently proven inefficient because microblog posts typically l…
Opinion MiningPersian Sentiment AnalysisSentiment AnalysisSentiment Classification+1Relational Temporal Graph Reasoning for Dual-task Dialogue Language Understanding
Dual-task dialog language understanding aims to tackle two correlative dialog language understanding tasks simultaneously via leveraging their inherent correlations. In this paper, we put forward a new framework, whose c…
Sentiment AnalysisSentiment Classificationweighted CapsuleNet networks for Persian multi-domain sentiment analysis
Sentiment classification is a fundamental task in natural language processing, assigning one of the three classes, positive, negative, or neutral, to free texts. However, sentiment classification models are highly domain…
Classificationdomain classificationSentiment AnalysisSentiment ClassificationBias Against 93 Stigmatized Groups in Masked Language Models and Downstream Sentiment Classification Tasks
The rapid deployment of artificial intelligence (AI) models demands a thorough investigation of biases and risks inherent in these models to understand their impact on individuals and society. This study extends the focu…
Sentiment AnalysisSentiment ClassificationPIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance
Although large language models (LLMs) has shown great performance on natural language processing (NLP) in the financial domain, there are no publicly available financial tailtored LLMs, instruction tuning datasets, and e…
Conversational Question AnsweringLanguage ModelingLanguage ModellingLarge Language Model+5Soft-prompt Tuning for Large Language Models to Evaluate Bias
Prompting large language models has gained immense popularity in recent years due to the advantage of producing good results even without the need for labelled data. However, this requires prompt tuning to get optimal pr…
FairnessLanguage ModelingLanguage ModellingSentiment Analysis+1UCAS-IIE-NLP at SemEval-2023 Task 12: Enhancing Generalization of Multilingual BERT for Low-resource Sentiment Analysis
This paper describes our system designed for SemEval-2023 Task 12: Sentiment analysis for African languages. The challenge faced by this task is the scarcity of labeled data and linguistic resources in low-resource setti…
Contrastive LearningRepresentation LearningSentiment AnalysisSentiment Classification+3Quantum Natural Language Processing based Sentiment Analysis using lambeq Toolkit
Sentiment classification is one the best use case of classical natural language processing (NLP) where we can witness its power in various daily life domains such as banking, business and marketing industry. We already k…
MarketingSentiment AnalysisSentiment ClassificationCharacterizing and Measuring Linguistic Dataset Drift
NLP models often degrade in performance when real world data distributions differ markedly from training data. However, existing dataset drift metrics in NLP have generally not considered specific dimensions of linguisti…
Natural Language InferenceSentiment AnalysisSentiment ClassificationZero-shot Approach to Overcome Perturbation Sensitivity of Prompts
Recent studies have demonstrated that natural-language prompts can help to leverage the knowledge learned by pre-trained language models for the binary sentence-level sentiment classification task. Specifically, these me…
ClassificationFew-Shot LearningSensitivitySentence+2Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text
Can language models transform inputs to protect text classifiers against adversarial attacks? In this work, we present ATINTER, a model that intercepts and learns to rewrite adversarial inputs to make them non-adversaria…
Adversarial RobustnessClassificationNews ClassificationSentiment Analysis+2Sentiment Analysis in the Era of Large Language Models: A Reality Check
Sentiment analysis (SA) has been a long-standing research area in natural language processing. It can offer rich insights into human sentiments and opinions and has thus seen considerable interest from both academia and …
Aspect-Based Sentiment AnalysisFew-Shot LearningSentiment AnalysisSentiment ClassificationPIEClass: Weakly-Supervised Text Classification with Prompting and Noise-Robust Iterative Ensemble Training
Weakly-supervised text classification trains a classifier using the label name of each target class as the only supervision, which largely reduces human annotation efforts. Most existing methods first use the label names…
Pseudo LabelSentiment AnalysisSentiment Classificationtext-classification+1Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals
Counterfactual Data Augmentation (CDA) is a commonly used technique for improving robustness in natural language classifiers. However, one fundamental challenge is how to discover meaningful counterfactuals and efficient…
counterfactualData AugmentationSentiment AnalysisSentiment Classification