With the increasingly crucial role played by electronic word-of-mouth, online reviews have become an indispensable informational element for multiple stakeholders in the competitive tourism market. However, the rapid development of generative artificial intelligence (GAI) has not only threatened the unique position of humans as the sole producers of reviews but also broken new ground in the covertness and disorientation of manipulated reviews. To address this emerging issue, this study proposes a novel detection system, namely, multi-modal GAI-manipulated tourism review detector, which can accurately detect both textual and visual tourism manipulation through the innovative extraction of text linguistic features and image texture patch features. The superiority and effectiveness of the proposed detection system are demonstrated through empirical system application. This study not only offers theoretical and methodological references for tourism review detection research, but also contributes to the decision-making of tourists, the reputation of tourism enterprises and online travel agents.

中文翻译：

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检测多模态 GAI 纵的旅游评论

随着电子口碑的作用越来越重要，在线评论已成为竞争激烈的旅游市场中多个利益相关者不可或缺的信息元素。然而，生成式人工智能 （GAI） 的快速发展不仅威胁到人类作为唯一评论生产者的独特地位，而且还在纵的评论的隐蔽性和迷失方向方面开辟了新天地。针对这一新出现的问题，本研究提出了一种新的检测系统，即多模态 GAI 纵的旅游评论检测器，它可以通过创新地提取文本语言特征和图像纹理补丁特征来准确检测文本和视觉旅游纵。通过实证系统应用证明了所提出的检测系统的优越性和有效性。本研究不仅为旅游点评检测研究提供了理论和方法论参考，而且为游客的决策、旅游企业和在线旅行社的声誉做出了贡献。