Papers Sentiment Classification
“Sentiment Classification” 태그가 달린 논문 949편 · 필터 해제
What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations
Adversarial attacks curated against NLP models are increasingly becoming practical threats. Although various methods have been developed to detect adversarial attacks, securing learning-based NLP systems in practice woul…
Abuse DetectionAdversarial TextAttributeSentiment Analysis+1AdvCodeMix: Adversarial Attack on Code-Mixed Data
Research on adversarial attacks are becoming widely popular in the recent years. One of the unexplored areas where prior research is lacking is the effect of adversarial attacks on code-mixed data. Therefore, in the pres…
Adversarial AttackSentenceSentiment AnalysisSentiment ClassificationImproved Multilingual Language Model Pretraining for Social Media Text via Translation Pair Prediction
We evaluate a simple approach to improving zero-shot multilingual transfer of mBERT on social media corpus by adding a pretraining task called translation pair prediction (TPP), which predicts whether a pair of cross-lin…
BenchmarkingLanguage ModelingLanguage ModellingNER+7Distributionally Robust Classifiers in Sentiment Analysis
In this paper, we propose sentiment classification models based on BERT integrated with DRO (Distributionally Robust Classifiers) to improve model performance on datasets with distributional shifts. We added 2-Layer Bi-L…
Sentiment AnalysisSentiment ClassificationLSA: Modeling Aspect Sentiment Coherency via Local Sentiment Aggregation
Aspect sentiment coherency is an intriguing yet underexplored topic in the field of aspect-based sentiment classification. This concept reflects the common pattern where adjacent aspects often share similar sentiments. D…
Adversarial DefenseAspect-Based Sentiment Analysis (ABSA)Sentiment ClassificationSentiment Dependency LearningSpan Detection for Aspect-Based Sentiment Analysis in Vietnamese
Aspect-based sentiment analysis plays an essential role in natural language processing and artificial intelligence. Recently, researchers only focused on aspect detection and sentiment classification but ignoring the sub…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Emotion RecognitionOpinion Mining+3Aspect-Sentiment-Multiple-Opinion Triplet Extraction
Aspect Sentiment Triplet Extraction (ASTE) aims to extract aspect term (aspect), sentiment and opinion term (opinion) triplets from sentences and can tell a complete story, i.e., the discussed aspect, the sentiment towar…
Aspect Sentiment Triplet ExtractionExtract AspectSentenceSentiment Analysis+2Using Psuedolabels for training Sentiment Classifiers makes the model generalize better across datasets
The problem statement addressed in this work is : For a public sentiment classification API, how can we set up a classifier that works well on different types of data, having limited ability to annotate data from across …
Sentiment AnalysisSentiment ClassificationBERT4GCN: Using BERT Intermediate Layers to Augment GCN for Aspect-based Sentiment Classification
Graph-based Aspect-based Sentiment Classification (ABSC) approaches have yielded state-of-the-art results, expecially when equipped with contextual word embedding from pre-training language models (PLMs). However, they i…
Sentiment AnalysisSentiment ClassificationHome Appliance Review Research Via Adversarial Reptile
For manufacturers of home appliances, the Studying discussion of products on social media can help manufacturers improve their products. Opinions provided through online reviews can immediately reflect whether the produc…
Aspect Category Sentiment ClassificationMeta-Learningnamed-entity-recognitionNamed Entity Recognition+4Aggregating User-Centric and Post-Centric Sentiments from Social Media for Topical Stance Prediction
Conventional opinion polls were usually conducted via questionnaires or phone interviews, which are time-consuming and error-prone. With the advances in social networking platforms, it’s easier for the general public to …
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)Sentiment Analysis+2A Corpus for Dimensional Sentiment Classification on YouTube Streaming Service
The streaming service platform such as YouTube provides a discussion function for audiences worldwide to share comments. YouTubers who upload videos to the YouTube platform want to track the performance of these uploaded…
Sentiment AnalysisSentiment ClassificationClassifying Tweet Sentiment Using the Hidden State and Attention Matrix of a Fine-tuned BERTweet Model
This paper introduces a study on tweet sentiment classification. Our task is to classify a tweet as either positive or negative. We approach the problem in two steps, namely embedding and classifying. Our baseline method…
ClassificationSentiment AnalysisSentiment ClassificationAdversarial Training: A simple and efficient technique to Improving NLP Robustness
NLP models are shown to be prone to adversarial attacks which undermines their robustness, i.e. a small perturbation to the input text can fool an NLP model to incorrectly classify text. In this study, we present a new A…
Adversarial TextAttributeSentiment AnalysisSentiment Classification+1Improving Sentiment Classification Using 0-Shot Generated Labels for Custom Transformer Embeddings
We present an approach to improve sentiment classification for transformers (based on BERT and DistilBERT) using additional embeddings to represent emotion inputs. We used HuggingFace's 0-shot prediction pipeline to gene…
ClassificationSentiment AnalysisSentiment ClassificationDecision Making For Celebrity Branding: An Opinion Mining Approach Based On Polarity And Sentiment Analysis Using Twitter Consumer-Generated Content (CGC)
The volume of discussions concerning brands within social media provides digital marketers with great opportunities for tracking and analyzing the feelings and views of consumers toward brands, products, influencers, ser…
BIG-bench Machine LearningDecision MakingOpinion MiningSentiment Analysis+1SentiPrompt: Sentiment Knowledge Enhanced Prompt-Tuning for Aspect-Based Sentiment Analysis
Aspect-based sentiment analysis (ABSA) is an emerging fine-grained sentiment analysis task that aims to extract aspects, classify corresponding sentiment polarities and find opinions as the causes of sentiment. The lates…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Language ModelingLanguage Modelling+4Dialog speech sentiment classification for imbalanced datasets
Speech is the most common way humans express their feelings, and sentiment analysis is the use of tools such as natural language processing and computational algorithms to identify the polarity of these feelings. Even th…
ClassificationSentiment AnalysisSentiment ClassificationTask-adaptive Pre-training and Self-training are Complementary for Natural Language Understanding
Task-adaptive pre-training (TAPT) and Self-training (ST) have emerged as the major semi-supervised approaches to improve natural language understanding (NLU) tasks with massive amount of unlabeled data. However, it's unc…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)Natural Language Inference+4Contrasting Human- and Machine-Generated Word-Level Adversarial Examples for Text Classification
Research shows that natural language processing models are generally considered to be vulnerable to adversarial attacks; but recent work has drawn attention to the issue of validating these adversarial inputs against cer…
Sentiment AnalysisSentiment Classificationtext-classificationText Classification+1