The study of tourism destination images is of great significance in the tourism discipline. Tourism user-generated content (UGC), i.e., the feedback on tourism websites, provides rich information for constructing a destination image. However, it is difficult for tourism researchers to obtain a relatively complete and intuitive destination image due to the unintuitive destination image display, the significant variance in departure time and data length, and the destination type in UGC. We propose TDIVis, a carefully designed visual analytics system, aimed at obtaining a relatively comprehensive destination image. Specifically, a keyword-based sentiment visualization method is proposed to associate the cognitive image with the emotional image, and by this method, both time evolution analysis and classification analysis are considered; a multi-attribute association double sequence visualization method is proposed to associate two different types of text sequences and provide a dynamic visual encoding interaction method for the multi-attribute characteristics of sequences. The effectiveness and usability of TDIVis are demonstrated through four cases and a user study.

对旅游目的地形象的研究在旅游学科中具有重要意义。旅游者用户生成的内容（UGC），即旅游者网站上的反馈，为构建目的地图像提供了丰富的信息。然而，由于目的地图像显示不直观，出发时间和数据长度的显着差异以及UGC中的目的地类型，旅游研究人员很难获得相对完整和直观的目的地图像。我们建议使用TDIVis，这是一种经过精心设计的视觉分析系统，旨在获得相对全面的目标图像。具体而言，提出了一种基于关键词的情感可视化方法，将认知图像和情感图像相关联，并同时考虑了时间演化分析和分类分析。提出了一种多属性关联双序列可视化方法来关联两种不同类型的文本序列，并为序列的多属性特征提供一种动态的可视编码交互方法。通过四个案例和一个用户研究证明了TDIVis的有效性和可用性。