Biased by Design? Evaluating Bias and Behavioral Diversity in LLM Annotation of Real-World and Synthetic Hotel Reviews

As large language models (LLMs) gain traction among researchers and practitioners, particularly in digital marketing for tasks such as customer feedback analysis and automated communication, concerns remain about the reliability and consistency of their outputs. This study investigates annotation bi...

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Bibliographic Details
Published in:	AI (Basel) Vol. 6; no. 8; p. 178
Main Authors:	Voutsa, Maria C., Tsapatsoulis, Nicolas, Djouvas, Constantinos
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.08.2025
Subjects:	AI bias Algorithms annotation bias Annotations Artificial intelligence aspect classification Automation Batch processing Behavior Bias Chatbots Datasets Decision making Hate speech Human error Labeling Labels Large language models Marketing Sentences Sentiment analysis Synthetic data topic modeling User generated content
ISSN:	2673-2688, 2673-2688
Online Access:	Get full text
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