Enhancing Multimodal Tourism Review Sentiment Analysis Through Advanced Feature Association Techniques

Peng Chen and Lingmei Fu
Additional contact information
Peng Chen: Sanya Institute of Technology, China
Lingmei Fu: Hainan Provincial Sports Academy, China

International Journal of Information Systems in the Service Sector (IJISSS), 2024, vol. 15, issue 1, 1-21

Abstract: The development of tourism services presents significant opportunities for extracting and analyzing customer sentiment. However, with the advent of multimodality, travel reviews have brought new challenges. Early methods for detecting such reviews merely combined text and image features, resulting in poor feature correlation. To address this issue, our study proposes a novel multimodal tourism review sentiment analysis method enhanced by relevant features. Initially, we employ a fusion model that combines BERT and Text-CNN for text feature extraction. This approach strengthens semantic relationships and filters noise effectively. Subsequently, we utilize ResNet-51 for image feature extraction, leveraging its ability to learn complex visual representations. Additionally, integrating an attention mechanism further enhances modality correlation, thereby improving fusion effectiveness. On the Multi-ZOL dataset, our method achieves an accuracy of 90.7% and an F1 score of 90.8%. Similarly, on the Ctrip dataset, it attains an accuracy of 83.6% and an F1 score of 84.1%.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJISSS.349564 (application/pdf)

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:igg:jisss0:v:15:y:2024:i:1:p:1-21

Access Statistics for this article

International Journal of Information Systems in the Service Sector (IJISSS) is currently edited by John Wang

More articles in International Journal of Information Systems in the Service Sector (IJISSS) from IGI Global
Bibliographic data for series maintained by Journal Editor ().