Dynamic Text Augmentation for Robust Sentiment Analysis: Enhancing Model Performance With EDA and Multi-Channel CNN
The rapid growth of social media has revolutionized the way individuals share and access opinions, generating vast amounts of textual data containing diverse sentiments. Sentiment analysis enables organizations to derive valuable insights from this data, facilitating improved decision-making. Howeve...
Saved in:
| Main Authors: | Komang Wahyu Trisna, Jinjie Huang, Yuanjian Chen, I Gede Juliana Eka Putra |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10870205/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Fusion Text Representations to Enhance Contextual Meaning in Sentiment Classification
by: Komang Wahyu Trisna, et al.
Published: (2024-11-01) -
A Review on Text Sentiment Analysis With Machine Learning and Deep Learning Techniques
by: Yonatan Mamani-Coaquira, et al.
Published: (2024-01-01) -
Comparative Study of Deep Learning-Based Sentiment Classification
by: Seungwan Seo, et al.
Published: (2020-01-01) -
Leveraging sentiment analysis of food delivery services reviews using deep learning and word embedding
by: Dheya Mustafa, et al.
Published: (2025-02-01) -
Examining Sentiment Analysis for Low-Resource Languages with Data Augmentation Techniques
by: Gaurish Thakkar, et al.
Published: (2024-11-01)