Enhanced twitter sentiment analysis with dual joint classifier integrating RoBERTa and BERT architectures
Sentiment analysis, a crucial aspect of Natural Language Processing (NLP), aims to extract subjective information from textual data. With the proliferation of social media platforms like Twitter, accurately determining public sentiment has become increasingly important for businesses, policymakers,...
Saved in:
| Main Author: | Luoyao He |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2024-12-01
|
| Series: | Frontiers in Physics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2024.1477714/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Sentiment analysis of movie reviews: A flask application using CNN with RoBERTa embeddings
by: Biplov Paneru, et al.
Published: (2025-12-01) -
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) -
Automatic Gender Identification from Text
by: Vladimir Younkin, et al.
Published: (2024-12-01) -
Electric Vehicle Sentiment Analysis Using Large Language Models
by: Hemlata Sharma, et al.
Published: (2024-11-01) -
Enhancing satellite-based emergency mapping: Identifying wildfires through geo-social media analysis
by: Sebastian Schmidt, et al.
Published: (2025-01-01)