3 papers
cs.AI2023
Modeling Uncertainty in Personalized Emotion Prediction with Normalizing Flows
Piotr Miłkowski, Konrad Karanowski, Patryk Wielopolski +3
Designing predictive models for subjective problems in natural language processing (NLP) remains challenging. This is mainly due to its non-deterministic nature and different perce…
cs.CL2023
From Big to Small Without Losing It All: Text Augmentation with ChatGPT for Efficient Sentiment Analysis
Stanisław Woźniak, Jan Kocoń
In the era of artificial intelligence, data is gold but costly to annotate. The paper demonstrates a groundbreaking solution to this dilemma using ChatGPT for text augmentation in…
cs.CL2023
Deep Emotions Across Languages: A Novel Approach for Sentiment Propagation in Multilingual WordNets
Jan Kocoń
Sentiment analysis involves using WordNets enriched with emotional metadata, which are valuable resources. However, manual annotation is time-consuming and expensive, resulting in…