Papers Sentiment Classification
“Sentiment Classification” 태그가 달린 논문 949편 · 필터 해제
AVSS: Layer Importance Evaluation in Large Language Models via Activation Variance-Sparsity Analysis
The evaluation of layer importance in deep learning has been an active area of research, with significant implications for model optimization and interpretability. Recently, large language models (LLMs) have gained promi…
Language ModelingLanguage ModellingLarge Language ModelModel Optimization+3Sentiment-Driven Community Detection in a Network of Perfume Preferences
Network analysis is increasingly important across various fields, including the fragrance industry, where perfumes are represented as nodes and shared user preferences as edges in perfume networks. Community detection ca…
Community DetectionGraph Clusteringgraph constructionMarketing+5Less is More: Parameter-Efficient Selection of Intermediate Tasks for Transfer Learning
Intermediate task transfer learning can greatly improve model performance. If, for example, one has little training data for emotion detection, first fine-tuning a language model on a sentiment classification dataset may…
AvgLanguage ModelingLanguage ModellingSentiment Analysis+2You Shall Know a Tool by the Traces it Leaves: The Predictability of Sentiment Analysis Tools
If sentiment analysis tools were valid classifiers, one would expect them to provide comparable results for sentiment classification on different kinds of corpora and for different languages. In line with results of prev…
Sentiment AnalysisSentiment ClassificationvalidExperiences from Creating a Benchmark for Sentiment Classification for Varieties of English
Existing benchmarks often fail to account for linguistic diversity, like language variants of English. In this paper, we share our experiences from our ongoing project of building a sentiment classification benchmark for…
DiversitySentiment AnalysisSentiment ClassificationComparing zero-shot self-explanations with human rationales in multilingual text classification
Instruction-tuned LLMs are able to provide an explanation about their output to users by generating self-explanations that do not require gradient computations or the application of possibly complex XAI methods. In this …
Multilingual text classificationSentiment AnalysisSentiment Classificationtext-classification+1Financial Sentiment Analysis on News and Reports Using Large Language Models and FinBERT
Financial sentiment analysis (FSA) is crucial for evaluating market sentiment and making well-informed financial decisions. The advent of large language models (LLMs) such as BERT and its financial variant, FinBERT, has …
ArticlesPrompt EngineeringSentiment AnalysisSentiment ClassificationExploring ChatGPT-based Augmentation Strategies for Contrastive Aspect-based Sentiment Analysis
Aspect-based sentiment analysis (ABSA) involves identifying sentiment towards specific aspect terms in a sentence and allows us to uncover nuanced perspectives and attitudes on particular aspects of a product, service, o…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Contrastive LearningData Augmentation+6Audio-Guided Fusion Techniques for Multimodal Emotion Analysis
In this paper, we propose a solution for the semi-supervised learning track (MER-SEMI) in MER2024. First, in order to enhance the performance of the feature extractor on sentiment classification tasks,we fine-tuned video…
Emotion RecognitionSelf-Supervised LearningSentiment AnalysisSentiment ClassificationAn Effective Deployment of Diffusion LM for Data Augmentation in Low-Resource Sentiment Classification
Sentiment classification (SC) often suffers from low-resource challenges such as domain-specific contexts, imbalanced label distributions, and few-shot scenarios. The potential of the diffusion language model (LM) for te…
Data AugmentationDiversityLanguage ModelingLanguage Modelling+2Masking The Bias : From Echo Chambers to Large Scale Aspect-Based Sentiment Analysis
Aspect-based sentiment analysis (ABSA) is a natural language processing (NLP) task, ascribing precise sentiment linkages to specific entities and issues in text data. This paper addresses critical shortcomings in current…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Community DetectionSentiment Analysis+1Instruct-DeBERTa: A Hybrid Approach for Aspect-based Sentiment Analysis on Textual Reviews
Aspect-based Sentiment Analysis (ABSA) is a critical task in Natural Language Processing (NLP) that focuses on extracting sentiments related to specific aspects within a text, offering deep insights into customer opinion…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Aspect ExtractionSentiment Analysis+2Great Memory, Shallow Reasoning: Limits of $k$NN-LMs
$K$-nearest neighbor language models ($k$NN-LMs), which integrate retrieval with next-word prediction, have demonstrated strong performance in language modeling as well as downstream NLP benchmarks. These results have le…
Language ModelingLanguage ModellingRetrievalSentiment Analysis+1BnSentMix: A Diverse Bengali-English Code-Mixed Dataset for Sentiment Analysis
The widespread availability of code-mixed data can provide valuable insights into low-resource languages like Bengali, which have limited datasets. Sentiment analysis has been a fundamental text classification task acros…
DiversitySentiment AnalysisSentiment Classificationtext-classification+1Ensemble BERT: A student social network text sentiment classification model based on ensemble learning and BERT architecture
The mental health assessment of middle school students has always been one of the focuses in the field of education. This paper introduces a new ensemble learning network based on BERT, employing the concept of enhancing…
Ensemble LearningSentiment AnalysisSentiment ClassificationDecoding Visual Sentiment of Political Imagery
How can we define visual sentiment when viewers systematically disagree on their perspectives? This study introduces a novel approach to visual sentiment analysis by integrating attitudinal differences into visual sentim…
Sentiment AnalysisSentiment ClassificationOptimal and efficient text counterfactuals using Graph Neural Networks
As NLP models become increasingly integral to decision-making processes, the need for explainability and interpretability has become paramount. In this work, we propose a framework that achieves the aforementioned by gen…
counterfactualDecision MakingSentiment AnalysisSentiment Classification+1Sentiment Reasoning for Healthcare
Transparency in AI healthcare decision-making is crucial. By incorporating rationales to explain reason for each predicted label, users could understand Large Language Models (LLMs)'s reasoning to make better decision. I…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Decision MakingMultimodal Sentiment Analysis+4Deep Learning-based Sentiment Analysis of Olympics Tweets
Sentiment analysis (SA), is an approach of natural language processing (NLP) for determining a text's emotional tone by analyzing subjective information such as views, feelings, and attitudes toward specific topics, prod…
Deep LearningSentiment AnalysisSentiment ClassificationNew Directions in Text Classification Research: Maximizing The Performance of Sentiment Classification from Limited Data
The stakeholders' needs in sentiment analysis for various issues, whether positive or negative, are speed and accuracy. One new challenge in sentiment analysis tasks is the limited training data, which often leads to sub…
ClassificationSentiment AnalysisSentiment Classificationtext-classification+1