[HTML][HTML] Sentiment analysis of the United States public support of nuclear power on social media using large language models
OH Kwon, K Vu, N Bhargava, MI Radaideh… - … and Sustainable Energy …, 2024 - Elsevier
This study utilized large language models (LLMs) to analyze public sentiment in the United
States (US) regarding nuclear power on social media, focusing on X/Twitter, considering …
States (US) regarding nuclear power on social media, focusing on X/Twitter, considering …
Enhancing author assessment: an advanced modified recursive elimination technique (MRET) for ranking key parameters and conducting statistical analysis of top …
Assessing the impact of authors in scientific research is crucial for evaluating scholarly
contributions. Various parameters exist in the literature to quantify researchers' productivity …
contributions. Various parameters exist in the literature to quantify researchers' productivity …
Deep Representation Learning of User Preferences for Opinionclassification
AUG Thennakoon Mudiyanselage, Y Li… - Available at SSRN … - papers.ssrn.com
Text classification assigns predefined categories to text using machine learning models
based onlearned patterns on extracted features. Feature-level sparsity occurs as not all …
based onlearned patterns on extracted features. Feature-level sparsity occurs as not all …
[PDF][PDF] A Comprehensive Performance Analysis of Supervised Machine Learning Techniques for Sentiment Analysis
K Matarat, C Mingmuang, W Charoenrat - International Journal of … - researchgate.net
Sentiment analysis plays a crucial role in deciphering opinions and emotions expressed in
textual data, with wide-ranging applications in business such as customer feedback analysis …
textual data, with wide-ranging applications in business such as customer feedback analysis …