Papers Subjectivity Analysis
“Subjectivity Analysis” 태그가 달린 논문 66편 · 필터 해제
Aligning LLM Uncertainty with Human Disagreement in Subjectivity Analysis
Large language models for subjectivity analysis are typically trained with aggregated labels, which compress variations in human judgment into a single supervision signal. This paradigm overlooks the intrinsic uncertaint…
Subjectivity AnalysisCreation of the Estonian Subjectivity Dataset: Assessing the Degree of Subjectivity on a Scale
This article presents the creation of an Estonian-language dataset for document-level subjectivity, analyzes the resulting annotations, and reports an initial experiment of automatic subjectivity analysis using a large l…
Subjectivity AnalysisDhati+: Fine-tuned Large Language Models for Arabic Subjectivity Evaluation
Despite its significance, Arabic, a linguistically rich and morphologically complex language, faces the challenge of being under-resourced. The scarcity of large annotated datasets hampers the development of accurate too…
Subjectivity AnalysisText ClassificationAI Wizards at CheckThat! 2025: Enhancing Transformer-Based Embeddings with Sentiment for Subjectivity Detection in News Articles
This paper presents AI Wizards' participation in the CLEF 2025 CheckThat! Lab Task 1: Subjectivity Detection in News Articles, classifying sentences as subjective/objective in monolingual, multilingual, and zero-shot set…
ArticlesSentenceSentiment AnalysisSubjectivity AnalysisCAPO: Cost-Aware Prompt Optimization
Large language models (LLMs) have revolutionized natural language processing by solving a wide range of tasks simply guided by a prompt. Yet their performance is highly sensitive to prompt formulation. While automated pr…
Arithmetic ReasoningAutoMLSentiment AnalysisSubjectivity Analysis+1Opinion Mining on Offshore Wind Energy for Environmental Engineering
In this paper, we conduct sentiment analysis on social media data to study mass opinion about offshore wind energy. We adapt three machine learning models, namely, TextBlob, VADER, and SentiWordNet because different func…
Data VisualizationOpinion MiningSentiment AnalysisSubjectivity AnalysisA Study of Nationality Bias in Names and Perplexity using Off-the-Shelf Affect-related Tweet Classifiers
In this paper, we apply a method to quantify biases associated with named entities from various countries. We create counterfactual examples with small perturbations on target-domain data instead of relying on templates …
Bias DetectioncounterfactualHate Speech DetectionSentence+1A Labelled Dataset for Sentiment Analysis of Videos on YouTube, TikTok, and Other Sources about the 2024 Outbreak of Measles
The work of this paper presents a dataset that contains the data of 4011 videos about the ongoing outbreak of measles published on 264 websites on the internet between January 1, 2024, and May 31, 2024. The dataset is av…
Sentiment AnalysisSubjectivity AnalysisVideo DescriptionCzech Dataset for Cross-lingual Subjectivity Classification
In this paper, we introduce a new Czech subjectivity dataset of 10k manually annotated subjective and objective sentences from movie reviews and descriptions. Our prime motivation is to provide a reliable dataset that ca…
ClassificationSubjectivity AnalysisDual Contrastive Learning: Text Classification via Label-Aware Data Augmentation
Contrastive learning has achieved remarkable success in representation learning via self-supervision in unsupervised settings. However, effectively adapting contrastive learning to supervised learning tasks remains as a …
ClassificationContrastive LearningData AugmentationRepresentation Learning+4Understanding the Role of Affect Dimensions in Detecting Emotions from Tweets: A Multi-task Approach
We propose VADEC, a multi-task framework that exploits the correlation between the categorical and dimensional models of emotion representation for better subjectivity analysis. Focusing primarily on the effective detect…
Emotion ClassificationregressionSubjectivity AnalysisEntailment as Few-Shot Learner
Large pre-trained language models (LMs) have demonstrated remarkable ability as few-shot learners. However, their success hinges largely on scaling model parameters to a degree that makes it challenging to train and serv…
Contrastive LearningData AugmentationFew-Shot LearningLinguistic Acceptability+7An Empirical Evaluation of Word Embedding Models for Subjectivity Analysis Tasks
It is a clearly established fact that good categorization results are heavily dependent on representation techniques. Text representation is a necessity that must be fulfilled before working on any text analysis task sin…
Language ModelingLanguage ModellingSubjectivity AnalysisCreating and Evaluating Resources for Sentiment Analysis in the Low-resource Language: Sindhi
In this paper, we develop Sindhi subjective lexicon using a merger of existing English resources: NRC lexicon, list of opinion words, SentiWordNet, Sindhi-English bilingual dictionary, and collection of Sindhi modifiers.…
Sentiment AnalysisSubjectivity Analysistext annotationLong-Distance Dependencies Don't Have to Be Long: Simplifying through Provably (Approximately) Optimal Permutations
Neural models at the sentence level often operate on the constituent words/tokens in a way that encodes the inductive bias of processing the input in a similar fashion to how humans do. However, there is no guarantee tha…
General ClassificationInductive BiasSentenceSubjectivity AnalysisVector of Locally-Aggregated Word Embeddings (VLAWE): A Novel Document-level Representation
In this paper, we propose a novel representation for text documents based on aggregating word embedding vectors into document embeddings. Our approach is inspired by the Vector of Locally-Aggregated Descriptors used for …
Multi-Label Text ClassificationSentiment AnalysisSubjectivity Analysistext-classification+2EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks
We present EDA: easy data augmentation techniques for boosting performance on text classification tasks. EDA consists of four simple but powerful operations: synonym replacement, random insertion, random swap, and random…
Data AugmentationGeneral ClassificationSentiment AnalysisSubjectivity Analysis+2Belittling the Source: Trustworthiness Indicators to Obfuscate Fake News on the Web
With the growth of the internet, the number of fake-news online has been proliferating every year. The consequences of such phenomena are manifold, ranging from lousy decision-making process to bullying and violence epis…
Fact CheckingFake News DetectionSubjectivity AnalysisWeb CredibilityTranslations as Additional Contexts for Sentence Classification
In sentence classification tasks, additional contexts, such as the neighboring sentences, may improve the accuracy of the classifier. However, such contexts are domain-dependent and thus cannot be used for another classi…
ClassificationGeneral ClassificationSentenceSentence Classification+2Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms
Many deep learning architectures have been proposed to model the compositionality in text sequences, requiring a substantial number of parameters and expensive computations. However, there has not been a rigorous evaluat…
Document ClassificationGeneral ClassificationNamed Entity Recognition (NER)Sentiment Analysis+3