Subjectivity Analysis
18 papers with code • 2 benchmarks • 2 datasets
A related task to sentiment analysis is the subjectivity analysis with the goal of labeling an opinion as either subjective or objective.
Benchmarks
These leaderboards are used to track progress in Subjectivity Analysis
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SUBJ
Most implemented papers
Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation
hiyouga/dual-contrastive-learning
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Contrastive learning has achieved remarkable success in representation learning via self-supervision in unsupervised settings.
Czech Dataset for Cross-lingual Subjectivity Classification
Our prime motivation is to provide a reliable dataset that can be used with the existing English dataset as a benchmark to test the ability of pre-trained multilingual models to transfer knowledge between Czech and English and vice versa.
Self-Adaptive Hierarchical Sentence Model
The ability to accurately model a sentence at varying stages (e. g., word-phrase-sentence) plays a central role in natural language processing.
Translations as Additional Contexts for Sentence Classification
rktamplayo/MCFA
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We are the first to use translations as domain-free contexts for sentence classification.
Belittling the Source: Trustworthiness Indicators to Obfuscate Fake News on the Web
To this aim, an important step to detect fake-news is to have access to a credibility score for a given information source.
Vector of Locally-Aggregated Word Embeddings (VLAWE): A Novel Document-level Representation
The Vector of Locally-Aggregated Word Embeddings (VLAWE) representation of a document is then computed by accumulating the differences between each codeword vector and each word vector (from the document) associated to the respective codeword.
An Empirical Evaluation of Word Embedding Models for Subjectivity Analysis Tasks
Ritika2001/Word-Embedding-Models-for-Subjectivity-Analysis
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IEEE International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) 2021
We obtained state-of-the-art results on the subjectivity task by fine-tuning the BERT Language Model.
Understanding the Role of Affect Dimensions in Detecting Emotions from Tweets: A Multi-task Approach
For the regression task, VADEC, when trained with SenWave, achieves 7. 6% and 16. 5% gains in Pearson Correlation scores over the current state-of-the-art on the EMOBANK dataset for the Valence (V) and Dominance (D) affect dimensions respectively.
