TDIVis：旅游目的地形象可视分析

曹梦琦; 梁晶; 李明召; 周峥澔; 朱敏

doi:10.1631/FITEE.1900631

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TDIVis：旅游目的地形象可视分析

智能可视化专题 | Updated：2022-05-19

- TDIVis：旅游目的地形象可视分析
- TDIVis: visual analysis of tourism destination images
- 信息与电子工程前沿（英文） 2020年21卷第4期页码：536-603
- Affiliations：
  
  College of Computer Science, Sichuan University, Chengdu 610065, China
  School of Science, RMIT University, Melbourne, Victoria 3000, Australia
  College of Engineering Science and Mechanics, Virginia Tech, Blacksburg, VA 24061, USA
- Author bio：
  
  [ "Meng-qi CAO, E-mail: mengqi.cao@scuvis.org" ]
  [ "Jing LIANG, E-mail: jing.liang@scuvis.org" ]
  [ "Ming-zhao LI, E-mail: mingzhao.li@rmit.eud.au" ]
  [ "Zheng-hao ZHOU, E-mail: zhenghao@vt.edu" ]
  Min ZHU, zhumin@scu.edu.cn
- Funds：
  
  the Science & Technology Department of Sichuan Province, China(2018GZ0171);the Chengdu Science and Technology Bureau, China(2015-HM01-00484-SF)
- DOI：10.1631/FITEE.1900631
  中图分类号： TP399
- 收稿：2019-11-18，
  
  修回：2020-;3-;6，
  
  纸质出版：2020-04
- Accepted：
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曹梦琦, 梁晶, 李明召, 等. TDIVis：旅游目的地形象可视分析[J]. 信息与电子工程前沿（英文）, 2020,21(4):536-603.

CAO Meng-qi, LIANG Jing, LI Ming-zhao, et al. TDIVis: visual analysis of tourism destination images[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(4): 536-603.
曹梦琦, 梁晶, 李明召, 等. TDIVis：旅游目的地形象可视分析[J]. 信息与电子工程前沿（英文）, 2020,21(4):536-603. DOI： 10.1631/FITEE.1900631.

CAO Meng-qi, LIANG Jing, LI Ming-zhao, et al. TDIVis: visual analysis of tourism destination images[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(4): 536-603. DOI： 10.1631/FITEE.1900631.

摘要

旅游目的地形象研究在旅游学科中具有重要意义。旅游用户生成内容（UGC），即旅游网站中的用户反馈，为构建目的地形象提供了丰富信息。然而，由于UGC中目的地形象展示不够直观，且旅行出发时间、文本长度和目的地形象类别差异较大，旅游研究者难以获得较为完整、直观的目的地形象。我们设计一个可视分析系统TDIVis，旨在获得一个相对全面的目的地形象。具体而言，提出一种基于关键字的情感可视化方法，关联认知形象与情感形象，同时兼顾时序演变分析和分类对比分析；提出一种多属性关联双序列可视化方法，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可视化编码交互方式。最后，通过4个案例和1个用户研究，验证TDIVis的有效性和可用性。

Abstract

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.

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