Papers Sentiment Classification
“Sentiment Classification” 태그가 달린 논문 949편 · 필터 해제
Bayes-enhanced Lifelong Attention Networks for Sentiment Classification
The classic deep learning paradigm learns a model from the training data of a single task and the learned model is also tested on the same task. This paper studies the problem of learning a sequence of tasks (sentiment c…
ClassificationSentiment AnalysisSentiment ClassificationModeling Local Contexts for Joint Dialogue Act Recognition and Sentiment Classification with Bi-channel Dynamic Convolutions
In this paper, we target improving the joint dialogue act recognition (DAR) and sentiment classification (SC) tasks by fully modeling the local contexts of utterances. First, we employ the dynamic convolution network (DC…
Language ModelingLanguage ModellingMulti-Task LearningSentiment Analysis+1Syntax-Aware Graph Attention Network for Aspect-Level Sentiment Classification
Aspect-level sentiment classification aims to distinguish the sentiment polarities over aspect terms in a sentence. Existing approaches mostly focus on modeling the relationship between the given aspect words and their c…
ClassificationGraph AttentionLanguage ModelingLanguage Modelling+3Label Correction Model for Aspect-based Sentiment Analysis
Aspect-based sentiment analysis includes opinion aspect extraction and aspect sentiment classification. Researchers have attempted to discover the relationship between these two sub-tasks and have proposed the joint mode…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Aspect Extractionmodel+3Aspect-Category based Sentiment Analysis with Hierarchical Graph Convolutional Network
Most of the aspect based sentiment analysis research aims at identifying the sentiment polarities toward some explicit aspect terms while ignores implicit aspects in text. To capture both explicit and implicit aspects, w…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Aspect Category DetectionSentiment Analysis+1Effective Few-Shot Classification with Transfer Learning
Few-shot learning addresses the the problem of learning based on a small amount of training data. Although more well-studied in the domain of computer vision, recent work has adapted the Amazon Review Sentiment Classific…
ClassificationFew-Shot LearningFew-Shot Text ClassificationSentiment Analysis+6MEISD: A Multimodal Multi-Label Emotion, Intensity and Sentiment Dialogue Dataset for Emotion Recognition and Sentiment Analysis in Conversations
Emotion and sentiment classification in dialogues is a challenging task that has gained popularity in recent times. Humans tend to have multiple emotions with varying intensities while expressing their thoughts and feeli…
Emotion RecognitionSentiment AnalysisSentiment ClassificationSUKHAN: Corpus of Hindi Shayaris annotated with Sentiment Polarity Information
Shayari is a form of poetry mainly popular in the Indian subcontinent, in which the poet expresses his emotions and feelings in a very poetic manner. It is one of the best ways to express our thoughts and opinions. There…
Sentiment AnalysisSentiment ClassificationOnly text? only image? or both? Predicting sentiment of internet memes
Nowadays, the spread of Internet memes on online social media platforms such as Instagram, Facebook, Reddit, and Twitter is very fast. Analyzing the sentiment of memes can provide various useful insights. Meme sentiment …
ClassificationMeme ClassificationSentiment AnalysisSentiment ClassificationDoes BERT Understand Sentiment? Leveraging Comparisons Between Contextual and Non-Contextual Embeddings to Improve Aspect-Based Sentiment Models
When performing Polarity Detection for different words in a sentence, we need to look at the words around to understand the sentiment. Massively pretrained language models like BERT can encode not only just the words in …
Aspect-Based Sentiment Analysis (ABSA)Language ModelingLanguage ModellingSentence+2Sentiment Classification in Bangla Textual Content: A Comparative Study
Sentiment analysis has been widely used to understand our views on social and political agendas or user experiences over a product. It is one of the cores and well-researched areas in NLP. However, for low-resource langu…
ClassificationGeneral ClassificationSentiment AnalysisSentiment ClassificationPalomino-Ochoa at SemEval-2020 Task 9: Robust System based on Transformer for Code-Mixed Sentiment Classification
We present a transfer learning system to perform a mixed Spanish-English sentiment classification task. Our proposal uses the state-of-the-art language model BERT and embed it within a ULMFiT transfer learning pipeline. …
Language ModelingLanguage ModellingSentiment AnalysisSentiment Classification+1Curriculum CycleGAN for Textual Sentiment Domain Adaptation with Multiple Sources
Sentiment analysis of user-generated reviews or comments on products and services in social networks can help enterprises to analyze the feedback from customers and take corresponding actions for improvement. To mitigate…
Domain AdaptationGenerative Adversarial NetworkSentiment AnalysisSentiment ClassificationRe-Assessing the "Classify and Count" Quantification Method
Learning to quantify (a.k.a.\ quantification) is a task concerned with training unbiased estimators of class prevalence via supervised learning. This task originated with the observation that "Classify and Count" (CC), t…
General ClassificationSentiment AnalysisSentiment ClassificationTweet Sentiment Quantification: An Experimental Re-Evaluation
Sentiment quantification is the task of training, by means of supervised learning, estimators of the relative frequency (also called ``prevalence'') of sentiment-related classes (such as \textsf{Positive}, \textsf{Neutra…
Sentiment AnalysisSentiment ClassificationOpinion Transmission Network for Jointly Improving Aspect-oriented Opinion Words Extraction and Sentiment Classification
Aspect-level sentiment classification (ALSC) and aspect oriented opinion words extraction (AOWE) are two highly relevant aspect-based sentiment analysis (ABSA) subtasks. They respectively aim to detect the sentiment pola…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)General ClassificationSentence+2Convolution over Hierarchical Syntactic and Lexical Graphs for Aspect Level Sentiment Analysis
The state-of-the-art methods in aspect-level sentiment classification have leveraged the graph based models to incorporate the syntactic structure of a sentence. While being effective, these methods ignore the corpus lev…
RelationSentenceSentiment AnalysisSentiment ClassificationInducing Target-Specific Latent Structures for Aspect Sentiment Classification
Aspect-level sentiment analysis aims to recognize the sentiment polarity of an aspect or a target in a comment. Recently, graph convolutional networks based on linguistic dependency trees have been studied for this task.…
ClassificationDependency ParsingGeneral ClassificationSentiment Analysis+1Diversified Multiple Instance Learning for Document-Level Multi-Aspect Sentiment Classification
Neural Document-level Multi-aspect Sentiment Classification (DMSC) usually requires a lot of manual aspect-level sentiment annotations, which is time-consuming and laborious. As document-level sentiment labeled data are …
General ClassificationMultiple Instance LearningSentiment AnalysisSentiment ClassificationSentiment Analysis of Tweets using Heterogeneous Multi-layer Network Representation and Embedding
Sentiment classification on tweets often needs to deal with the problems of under-specificity, noise, and multilingual content. This study proposes a heterogeneous multi-layer network-based representation of tweets to ge…
General ClassificationSentiment AnalysisSentiment ClassificationSpecificity