Article: Evaluation of cultural tourism short-video dissemination effectiveness based on a multimodal transformer Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.54 pp.85 - 101 Abstract: In view of the increasing role of culture and tourism in promoting tourism, it is an urgent issue to assess exactly how effective they are. In this paper, a multi-modality transformer-based model is proposed to evaluate the communication efficiency of cultural and tourist videos. This model combines VI, BERT and MFCC for the extraction of image, text and audio characteristics. Cross-modal attention and consistency constraints can be used to improve the convergence of information. In order to verify the effectiveness of the proposed model, a series of experiments were carried out to evaluate the performance of the proposed model, such as user engagement, dissemination breadth, and sentiment fluctuation. Experimental results show that the prediction accuracy of the proposed model is 89.2%, the prediction of user interaction is 87.1%, and the correlation coefficient is 0.78. Compared with the conventional single-mode model, the performance of this model is significantly improved, which indicates that multimodal data fusion plays an important role in the evaluation of communication efficiency. Inderscience Publishers - linking academia, business and industry through research

Title: Evaluation of cultural tourism short-video dissemination effectiveness based on a multimodal transformer

Authors: Ning Shuo

Addresses: Television School, Communication University of China, Beijing, 100024, China; College of Liberal Arts & Journalism, Inner Mongolia University, Huhhot 010021, Inner Mongolia, China

Abstract: In view of the increasing role of culture and tourism in promoting tourism, it is an urgent issue to assess exactly how effective they are. In this paper, a multi-modality transformer-based model is proposed to evaluate the communication efficiency of cultural and tourist videos. This model combines VI, BERT and MFCC for the extraction of image, text and audio characteristics. Cross-modal attention and consistency constraints can be used to improve the convergence of information. In order to verify the effectiveness of the proposed model, a series of experiments were carried out to evaluate the performance of the proposed model, such as user engagement, dissemination breadth, and sentiment fluctuation. Experimental results show that the prediction accuracy of the proposed model is 89.2%, the prediction of user interaction is 87.1%, and the correlation coefficient is 0.78. Compared with the conventional single-mode model, the performance of this model is significantly improved, which indicates that multimodal data fusion plays an important role in the evaluation of communication efficiency.

Keywords: multimodal learning; cross-modal fusion; short video marketing; emotional fluctuation analysis; cultural tourism dissemination; sentiment analysis; user behaviour analysis.

DOI: 10.1504/IJICT.2026.153718

International Journal of Information and Communication Technology, 2026 Vol.27 No.54, pp.85 - 101

Received: 05 Feb 2026
Accepted: 11 Mar 2026
Published online: 21 May 2026 *

Title: Evaluation of cultural tourism short-video dissemination effectiveness based on a multimodal transformer

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