Comparing large Language models and human annotators in latent content analysis of sentiment, political leaning, emotional intensity and sarcasm

Comparing large Language models and human annotators in latent content analysis of sentiment, political leaning, emotional intensity and sarcasm

Abstract In the era of rapid digital communication, vast amounts of textual data are generated daily, demanding efficient methods for latent content analysis to extract meaningful insights. Large Language Models (LLMs) offer potential for automating this process, yet comprehensive assessments compar...

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Bibliographic Details
Main Authors: Ljubiša Bojić, Olga Zagovora, Asta Zelenkauskaite, Vuk Vuković, Milan Čabarkapa, Selma Veseljević Jerković, Ana Jovančević
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Large Language models
Latent content analysis
Humans vs. AI
Sentiment analysis
Political leaning
Online Access:https://doi.org/10.1038/s41598-025-96508-3
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https://doi.org/10.1038/s41598-025-96508-3

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