Papers Sentiment Classification
“Sentiment Classification” 태그가 달린 논문 949편 · 필터 해제
Example-based Hypernetworks for Out-of-Distribution Generalization
As Natural Language Processing (NLP) algorithms continually achieve new milestones, out-of-distribution generalization remains a significant challenge. This paper addresses the issue of multi-source adaptation for unfami…
DecoderDomain AdaptationNatural Language InferenceOut-of-Distribution Generalization+2A Survey on Aspect-Based Sentiment Classification
With the constantly growing number of reviews and other sentiment-bearing texts on the Web, the demand for automatic sentiment analysis algorithms continues to expand. Aspect-based sentiment classification (ABSC) allows …
ClassificationSentiment AnalysisSentiment ClassificationSurveyMulti-channel CNN to classify nepali covid-19 related tweets using hybrid features
Because of the current COVID-19 pandemic with its increasing fears among people, it has triggered several health complications such as depression and anxiety. Such complications have not only affected the developed count…
ClassificationSentiment AnalysisSentiment ClassificationCan Pre-trained Language Models Interpret Similes as Smart as Human?
Simile interpretation is a crucial task in natural language processing. Nowadays, pre-trained language models (PLMs) have achieved state-of-the-art performance on many tasks. However, it remains under-explored whether PL…
Sentiment AnalysisSentiment ClassificationCombining dynamic local context focus and dependency cluster attention for aspect-level sentiment classification
Aspect-level sentiment classification (ASC), as a subtask of Aspect-based sentiment analysis (ABSA), aims to analyze the sentiment polarity of different aspect terms in a sentence. Although the existing methods have been…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)SentenceSentiment Analysis+1DARER: Dual-task Temporal Relational Recurrent Reasoning Network for Joint Dialog Sentiment Classification and Act Recognition
The task of joint dialog sentiment classification (DSC) and act recognition (DAR) aims to simultaneously predict the sentiment label and act label for each utterance in a dialog. In this paper, we put forward a new frame…
Dialog Act ClassificationGPURelational ReasoningSentiment Analysis+1TraceNet: Tracing and Locating the Key Elements in Sentiment Analysis
In this paper, we study sentiment analysis task where the outcomes are mainly contributed by a few key elements of the inputs. Motivated by the two-streams hypothesis, we propose a neural architecture, named TraceNet, to…
Sentiment AnalysisSentiment ClassificationDomain-level Pairwise Semantic Interaction for Aspect-Based Sentiment Classification
Aspect-based sentiment classification (ABSC) is a very challenging subtask of sentiment analysis (SA) and suffers badly from the class-imbalance. Existing methods only process sentences independently, without considering…
ClassificationSentenceSentiment AnalysisSentiment ClassificationUsing Random Perturbations to Mitigate Adversarial Attacks on Sentiment Analysis Models
Attacks on deep learning models are often difficult to identify and therefore are difficult to protect against. This problem is exacerbated by the use of public datasets that typically are not manually inspected before u…
Sentiment AnalysisSentiment ClassificationSpelling CorrectionZero-Shot Aspect-Based Sentiment Analysis
Aspect-based sentiment analysis (ABSA) typically requires in-domain annotated data for supervised training/fine-tuning. It is a big challenge to scale ABSA to a large number of new domains. This paper aims to train a uni…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Aspect ExtractionNatural Language Inference+2GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games
Explaining machine learning models is an important and increasingly popular area of research interest. The Shapley value from game theory has been proposed as a prime approach to compute feature importance towards model …
AttributeFeature ImportanceGraph Property PredictionProperty Prediction+2Sentiment-Aware Automatic Speech Recognition pre-training for enhanced Speech Emotion Recognition
We propose a novel multi-task pre-training method for Speech Emotion Recognition (SER). We pre-train SER model simultaneously on Automatic Speech Recognition (ASR) and sentiment classification tasks to make the acoustic …
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)ClassificationEmotion Recognition+5STT: Soft Template Tuning for Few-Shot Learning
With the rapid expansion of large pre-trained language models, fine-tuning all the model parameters for downstream tasks is becoming computationally prohibitive. The recently developed prompt-based methods freeze the ent…
Few-Shot LearningLanguage ModelingLanguage ModellingMasked Language Modeling+2Lexicon based Fine-tuning of Multilingual Language Models for Sentiment Analysis of Low-resource Languages
Massively multilingual language models (MMLM) such as mBERT and XLM-R have shown good cross-lingual transferability. However, they are not specifically trained to capture cross-lingual signals with respect to sentiment w…
ClassificationSentiment AnalysisSentiment ClassificationXLM-RTraceNet: Tracing and Locating the Key Elements in Sentiment Analysis
In this paper, we study sentiment analysis task where the outcomes are mainly contributed by a few key elements of the inputs. Motivated by the two-streams hypothesis, we propose a neural architecture, named TraceNet, to…
Sentiment AnalysisSentiment ClassificationAuto-ABSA: Cross-Domain Aspect Detection and Sentiment Analysis Using Auxiliary Sentences
After transformer is proposed, lots of pre-trained language models have been come up with and sentiment analysis (SA) task has been improved. In this paper, we proposed a method that uses an auxiliary sentence about aspe…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)SentenceSentiment Analysis+1DigNet: Digging Clues from Local-Global Interactive Graph for Aspect-level Sentiment Classification
In aspect-level sentiment classification (ASC), state-of-the-art models encode either syntax graph or relation graph to capture the local syntactic information or global relational information. Despite the advantages of …
RelationSentiment AnalysisSentiment ClassificationDomain Adaptation with Category Attention Network for Deep Sentiment Analysis
Domain adaptation tasks such as cross-domain sentiment classification aim to utilize existing labeled data in the source domain and unlabeled or few labeled data in the target domain to improve the performance in the tar…
AttributeClassificationDomain AdaptationSentiment Analysis+1Continual Learning with Knowledge Transfer for Sentiment Classification
This paper studies continual learning (CL) for sentiment classification (SC). In this setting, the CL system learns a sequence of SC tasks incrementally in a neural network, where each task builds a classifier to classif…
ClassificationContinual LearningNatural QuestionsSentiment Analysis+2A Novel Approach for Enhancing Sentiment Classification of Persian Reviews Using Convolutional Neural Network and Majority Voting Classifier
Due to the rapid development of Internet-based applications such as social media, sentiment analysis has become one of the most widely used research areas of natural language processing and an important tool for extracti…
Ensemble LearningMajority Voting ClassifierPersian Sentiment AnalysisSentiment Analysis+1