MDIVis:对旅游用户生成内容的多个目的地图像进行可视化分析

IF 3.8 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Changlin Li , Mengqi Cao , Xiaolin Wen , Haotian Zhu , Shangsong Liu , Xinyi Zhang , Min Zhu
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引用次数: 2

摘要

丰富的旅游用户生成内容(UGC)包含了丰富的认知和情感信息,为构建描绘游客在旅游过程中的体验和对目的地的评价的目的地形象提供了宝贵的数据。特别是,多元目的地形象可以帮助旅游管理者挖掘共性和差异性,调查游客的兴趣要素,提高目的地的竞争力。然而,现有的方法通常只关注单个目的地的形象,不足以对UGC进行分析和可视化,提取有价值的信息和知识。因此,我们与旅游专家讨论了需求,并提出了MDIVis,这是一个多层次的交互式视觉分析系统,可以让分析师理解和分析多个目的地图像的认知主题和情感体验,以便进行比较。具体而言,我们设计了一种新的情感矩阵视图来总结多个目的地图像,并改进了两种经典视图来分析时间序列模式和比较图像的详细信息。最后,我们通过与领域专家对真实数据的三个案例研究来证明MDIVis的实用性,并通过专家访谈来证实其可用性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MDIVis: Visual analytics of multiple destination images on tourism user generated content

Abundant tourism user-generated content (UGC) contains a wealth of cognitive and emotional information, providing valuable data for building destination images that depict tourists’ experiences and appraisal of the destinations during the tours. In particular, multiple destination images can assist tourism managers in exploring the commonalities and differences to investigate the elements of interest of tourists and improve the competitiveness of the destinations. However, existing methods usually focus on the image of a single destination, and they are not adequate to analyze and visualize UGC to extract valuable information and knowledge. Therefore, we discuss requirements with tourism experts and present MDIVis, a multi-level interactive visual analytics system that allows analysts to comprehend and analyze the cognitive themes and emotional experiences of multiple destination images for comparison. Specifically, we design a novel sentiment matrix view to summarize multiple destination images and improve two classic views to analyze the time-series pattern and compare the detailed information of images. Finally, we demonstrate the utility of MDIVis through three case studies with domain experts on real-world data, and the usability and effectiveness are confirmed through expert interviews.

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来源期刊
Visual Informatics
Visual Informatics Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
6.70
自引率
3.30%
发文量
33
审稿时长
79 days
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