Evaluation of the Development Value of Emotional Data Mining in Mass Media Using the RBTM Model
With the proliferation of the internet, many social platforms continue to emerge, giving rise to a surge in user-generated content. Consequently, abundant textual information permeates the virtual realm, wielding a certain impact on public opinion orientation. One can discern the prevailing sentimen...
Main Author: | Wenbin Yang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10215383/ |
Similar Items
-
Sentiment Analysis With Ensemble Hybrid Deep Learning Model
by: Kian Long Tan, et al.
Published: (2022-01-01) -
T5 for Hate Speech, Augmented Data, and Ensemble
by: Tosin Adewumi, et al.
Published: (2023-09-01) -
Study on the Qualitative Cohesion in Bitcoin Market Price Prediction
by: Namjae Cho, et al.
Published: (2024-01-01) -
RB_BG_MHA: A RoBERTa-Based Model with Bi-GRU and Multi-Head Attention for Chinese Offensive Language Detection in Social Media
by: Meijia Xu, et al.
Published: (2023-10-01) -
Hybrid Approach to Automated Essay Scoring: Integrating Deep Learning Embeddings with Handcrafted Linguistic Features for Improved Accuracy
by: Muhammad Faseeh, et al.
Published: (2024-10-01)