Резултати

eNauka >  Results >  Comparing large Language models and human annotators in latent content analysis of sentiment, political leaning, emotional intensity and sarcasm
Title: Comparing large Language models and human annotators in latent content analysis of sentiment, political leaning, emotional intensity and sarcasm
Authors: Bojic, Ljubisa  ; Zagovora, Olga; Zelenkauskaite, Asta; Vuković, Vuk; Čabarkapa, Milan; Veseljević Jerković, Selma; Jovančević, Ana
Issue Date: 2025
Publication: Scientific Reports
ISSN: 2045-2322 Scientific Reports Search Idenfier
Publisher: Nature Research
Type: Article
Collation: vol. 15 br. 1
DOI: 10.1038/s41598-025-96508-3
WoS-ID: 001459325700008
Scopus-ID: 2-s2.0-105002820343
URI: https://rifdt.ifdt.bg.ac.rs/123456789/4305
https://enauka.gov.rs/handle/123456789/977609
Project: CA21129 - What are Opinions? Integrating Theory and Methods for Automatically Analyzing Opinionated Communication (OPINION)
M-category: 
21M21

31
SCOPUSTM
21
WEB OF SCIENCETM
Алт метрика
Dimensions
Unpaywall

Creative Commons лиценца