Papers Sentiment Classification
“Sentiment Classification” 태그가 달린 논문 949편 · 필터 해제
Feedforward Legendre Memory Unit
Recently, a new recurrent neural network (RNN) named the Legendre Memory Unit (LMU) was proposed and shown to achieve state-of-the-art performance on psMNIST and other datasets. Here we consider a modified version of the…
image-classificationImage ClassificationNatural Language InferenceQQP+4TextTN: Probabilistic Encoding of Language on Tensor Network
As a novel model that bridges machine learning and quantum theory, tensor network (TN) has recently gained increasing attention and successful applications for processing natural images. However, for natural languages, i…
General ClassificationSentenceSentiment AnalysisSentiment Classification+2Aspect-based Sentiment Classification via Reinforcement Learning
Aspect-based sentiment classification aims to predict sentimental polarities of one or multiple aspects in texts. As texts always contain a large proportion of task-irrelevant words, accurate alignment between aspects an…
ClassificationGeneral Classificationreinforcement-learningReinforcement Learning+3Learn2Weight: Weights Transfer Defense against Similar-domain Adversarial Attacks
Recent work in black-box adversarial attacks for NLP systems has attracted attention. Prior black-box attacks assume that attackers can observe output labels from target models based on selected inputs. In this work, ins…
Adversarial AttackDomain AdaptationMulti-Domain Sentiment ClassificationSentiment Analysis+1Explaining NLP Models via Minimal Contrastive Editing (MiCE)
Humans have been shown to give contrastive explanations, which explain why an observed event happened rather than some other counterfactual event (the contrast case). Despite the influential role that contrastivity plays…
counterfactualMultiple-choiceQuestion AnsweringSentiment Analysis+2Co-GAT: A Co-Interactive Graph Attention Network for Joint Dialog Act Recognition and Sentiment Classification
In a dialog system, dialog act recognition and sentiment classification are two correlative tasks to capture speakers intentions, where dialog act and sentiment can indicate the explicit and the implicit intentions separ…
Graph AttentionSentiment AnalysisSentiment ClassificationBuilding domain specific lexicon based on TikTok comment dataset
In the sentiment analysis task, predicting the sentiment tendency of a sentence is an important branch. Previous research focused more on sentiment analysis in English, for example, analyzing the sentiment tendency of se…
SentenceSentiment AnalysisSentiment ClassificationMulti-Aspect Sentiment Analysis with Latent Sentiment-Aspect Attribution
In this paper, we introduce a new framework called the sentiment-aspect attribution module (SAAM). SAAM works on top of traditional neural networks and is designed to address the problem of multi-aspect sentiment classif…
SentenceSentiment AnalysisSentiment Classification"Let's Eat Grandma": Does Punctuation Matter in Sentence Representation?
Neural network-based embeddings have been the mainstream approach for creating a vector representation of the text to capture lexical and semantic similarities and dissimilarities. In general, existing encoding methods d…
SentenceSentiment AnalysisSentiment ClassificationCross-Domain Sentiment Classification with In-Domain Contrastive Learning
Contrastive learning (CL) has been successful as a powerful representation learning method. In this paper, we propose a contrastive learning framework for cross-domain sentiment classification. We aim to induce domain in…
ClassificationContrastive LearningGeneral ClassificationRepresentation Learning+2Sentiment analysis in Bengali via transfer learning using multi-lingual BERT
Sentiment analysis (SA) in Bengali is challenging due to this Indo-Aryan language's highly inflected properties with more than 160 different inflected forms for verbs and 36 different forms for noun and 24 different form…
Sentiment AnalysisSentiment ClassificationTransfer LearningHow Can I Explain This to You? An Empirical Study of Deep Neural Network Explanation Methods
Explaining the inner workings of deep neural network models have received considerable attention in recent years. Researchers have attempted to provide human parseable explanations justifying why a model performed a spec…
General ClassificationSentiment AnalysisSentiment ClassificationBAN-ABSA: An Aspect-Based Sentiment Analysis dataset for Bengali and it's baseline evaluation
Due to the breathtaking growth of social media or newspaper user comments, online product reviews comments, sentiment analysis (SA) has captured substantial interest from the researchers. With the fast increase of domain…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)SentenceSentiment Analysis+2NLP\_UIOWA at SemEval-2020 Task 8: You're Not the Only One Cursed with Knowledge - Multi Branch Model Memotion Analysis
We propose hybrid models (HybridE and HybridW) for meme analysis (SemEval 2020 Task 8), which involves sentiment classification (Subtask A), humor classification (Subtask B), and scale of semantic classes (Subtask C). Th…
ClassificationSentiment AnalysisSentiment ClassificationBennettNLP at SemEval-2020 Task 8: Multimodal sentiment classification Using Hybrid Hierarchical Classifier
Memotion analysis is a very crucial and important subject in today{'}s world that is dominated by social media. This paper presents the results and analysis of the SemEval-2020 Task-8: Memotion analysis by team Kraken th…
Multimodal Sentiment AnalysisOptical Character Recognition (OCR)Sentiment AnalysisSentiment ClassificationMemebusters at SemEval-2020 Task 8: Feature Fusion Model for Sentiment Analysis on Memes Using Transfer Learning
In this paper, we describe our deep learning system used for SemEval 2020 Task 8: Memotion analysis. We participated in all the subtasks i.e Subtask A: Sentiment classification, Subtask B: Humor classification, and Subta…
Sentiment AnalysisSentiment ClassificationTransfer LearningSIS@IIITH at SemEval-2020 Task 8: An Overview of Simple Text Classification Methods for Meme Analysis
Memes are steadily taking over the feeds of the public on social media. There is always the threat of malicious users on the internet posting offensive content, even through memes. Hence, the automatic detection of offen…
ClassificationOptical Character Recognition (OCR)Sentiment AnalysisSentiment Classification+2UI at SemEval-2020 Task 8: Text-Image Fusion for Sentiment Classification
This paper describes our system, UI, for task A: Sentiment Classification in SemEval-2020 Task 8 Memotion Analysis. We use a common traditional machine learning, which is SVM, by utilizing the combination of text and ima…
Language ModelingLanguage ModellingSentiment AnalysisSentiment ClassificationUoR at SemEval-2020 Task 8: Gaussian Mixture Modelling (GMM) Based Sampling Approach for Multi-modal Memotion Analysis
Memes are widely used on social media. They usually contain multi-modal information such as images and texts, serving as valuable data sources to analyse opinions and sentiment orientations of online communities. The pro…
Sentiment AnalysisSentiment ClassificationUrszula Wali\'nska at SemEval-2020 Task 8: Fusion of Text and Image Features Using LSTM and VGG16 for Memotion Analysis
In this paper, we describe the entry to the task of Memotion Analysis. The sentiment analysis of memes task, is motivated by a pervasive problem of offensive content spread in social media, up to the present time. In fac…
Sentiment AnalysisSentiment Classification