大数据环境下的旅游目的地形象研究综述:数据、方法和技术

A Review of Tourist Destination Image in the Big Data Era:Data,Methods,and Technology

本文通过收集和筛选发表在科学引文索引(SCI)、社会科学引文索引(SSCI)和北大中文核心期刊目录(2020版)中与大数据环境下旅游目的地形象研究相关的文献,从数据(来源和模态)、方法和技术(工具)3个视角分析总结现有研究,展望未来研究趋势。研究显示:用户生成内容是主要的数据来源,文本模态数据占据主导地位;内容分析法是大数据环境下旅游目的地形象研究的基本方法,情感分析、主题建模、图像标注、图像识别等其他常用的计算机科学领域方法亦可归入此类;技术上,主要通过自然语言处理技术对文本进行分析,深度学习技术逐渐应用于图片和视频数据分析领域;工具上,主要使用带有图形用户界面的数据分析软件进行分析以及通过编程调用平台或模块开展研究。

By collecting and screening 74 papers related to tourist destination image research in the big data environment—and published in the Science Citation Index(SCI),Social Science Citation Index(SSCI),and Peking University Chinese Core Journal Catalog(2020 Edition),as of April 2023—this study combs through the current status of the field,and analyzes and summarizes existing research from three perspectives—data(sources and modalities),methodology,and technology(tools)—and looks forward to future research trends.The research shows that user-generated content is the main data source,textual data is dominant in terms of modality,and content analysis is the basic method of tourist destination image research in the big data environment.Other commonly used methods in the fi eld of computer science—such as sentiment analysis,topic modeling,image annotation,and image recognition—can also be classifi ed into this category.Technically,application programming interfaces(APIs)and software tools are mostly used,and the application of deep learning mainly focuses on image data,which has not yet been fully investigated in research on the image of tourist destinations.