Improving Turkish Text Sentiment Classification Through Task-Specific and Universal Transformations: An Ensemble Data Augmentation Approach

Improving Turkish Text Sentiment Classification Through Task-Specific and Universal Transformations: An Ensemble Data Augmentation Approach

The exponential growth of digital data in recent years has spurred a significant interest in natural language processing (NLP) and sentiment analysis. However, the effectiveness of NLP models heavily relies on the availability of large, annotated datasets, which are often scarce or entirely absent f...

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Bibliographic Details
Main Authors: Aytug Onan, Kadriye Filiz Balbal
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Text classification
sentiment analysis
ensemble learning
deep learning
Online Access:https://ieeexplore.ieee.org/document/10380566/

Internet

https://ieeexplore.ieee.org/document/10380566/

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