Generative AI for Sentiment Analysis

Stanislav Ivanov (), Katerina Volchek and Celso Brito
Additional contact information
Stanislav Ivanov: Varna University of Management
Katerina Volchek: Deggendorf Institute of Technology
Celso Brito: Deggendorf Institute of Technology

A chapter in Information and Communication Technologies in Tourism 2025, 2025, pp 129-139 from Springer

Abstract: Abstract As a valuable tool for tourism, sentiment analysis requires in-depth knowledge of linguistics and research context, as well as substantial time and monetary investments. The existing tools aiming at sentiment analysis automation generally lack validity compared to the manual analysis. However, contemporary technologies create new opportunities for Natural Language Processing and, therefore, sentiment analysis. This paper evaluates the effectiveness of GenAI for sentiment analysis and benchmarks it against two alternative coding approaches—manual coding and NVivo. The paper uses 301 online customer reviews of hotels implementing service robots in their front-end operations. The results show that ChatGPT systematically outperforms NVivo but falls short compared to manual coding. Both ChatGPT and NVivo correctly identify positive and negative emotions in most reviews. However, both fail to distinguish the degree of polarity and avoid extreme sentiments (very positive/negative). Further investigation and improvement of sentiment analysis tools are required.

Keywords: Sentiment analysis; ChatGPT; Generative AI; Research automation; Tourism (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-83705-0_11

Ordering information: This item can be ordered from
http://www.springer.com/9783031837050

DOI: 10.1007/978-3-031-83705-0_11

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().