Tourism destination image and its influencing factors based on multi-source heterogeneous reviews:

doi:10.3969/j.issn.1004-9479.2024.10.20230233

Abstract

Abstract:

Comments on both community-based and transaction-based platforms include tourism attractions, tourism services, and tourist emotions, but whether these two types will lead to similarities and differences in the overall image and segmented image is a proposition worth exploring. Based on the three-dimensional model of "cognition-emotion-integrity", Lijiang ancient city was used as the case area, Sina Weibo and Ctrip reviews representing community-based and transactional data respectively were used as the research data, combined with Python programming to call Baidu Sentiment Dictionary sentiment analysis method, used LDA to refine image themes, and constructed a co-occurrence relationship network map combining VOSviewer and Gephi to Analyze the similarities and differences between two types of data-driven overall image, cognitive image and emotional image and their influencing factors. The results show that 1) The overall image of destinations based on Sina Weibo's community-based and Ctrip's transaction-based reviews is mainly positive, with similar changes in annual image changes, and the distribution of emotional polarity is basically the same. 2) Although both community-based and transaction-based reviews can reflect cognitive and emotional image themes such as destination services, attractions, and environmental economy, the cognitive image theme score of the former is significantly higher than that of the latter, while the emotional image is the opposite. 3) There is little difference in the contribution rate of cognitive and emotional factors to the overall image of the destination driven by the two kinds of review data, while the effect of the economic price factor of the transaction type review is significantly higher than that of the community type review. The research provides a certain reference basis for using large-scale multi-source heterogeneous data to analyze destination image and tourism marketing work.

Key words: tourism destination image, multi-source data, sentiment analysis, LDA, the Old Town of Lijiang

摘要：

社区型和交易型平台的评论都包含旅游吸引物、旅游服务、游客情感等内容，但这两种类型是否会导致旅游目的地的整体形象和细分形象出现异同是一个值得探讨的命题。基于“认知-情感-整体”三维模型，以丽江古城为案例区，利用分别代表社区型和交易型数据的新浪微博和携程评论为研究数据，结合Python编程调用百度情感词典情感分析方法，利用LDA提炼形象主题，并构建VOSviewer与Gephi相结合的共现关系网络图谱，分析两类数据驱动的整体形象、认知形象和情感形象的异同及其影响因素。结果表明：1）基于新浪微博社区型和携程交易型评论的目的地整体形象都以正面为主，年度形象变化具有一定的相似性，情感极性分布基本一致。2）社区型和交易型评论虽都能体现出目的地服务、吸引物、环境经济等认知和情感方面的形象主题，但前者的认知形象主题评分明显高于后者，而情感形象则截然相反。3）认知和情感因素对两类评论数据驱动的目的地整体形象的贡献率总体相差较小，而交易型评论的经济价格因素所起的作用显著高于社区型评论。研究为利用大规模的多源异构数据分析目的地形象和旅游营销工作提供了一定的参考依据。

关键词: 旅游目的地形象, 多源数据, 情感分析, LDA, 丽江古城

Zehai HE, Yuguo TAO, Hongxia ZHANG. Tourism destination image and its influencing factors based on multi-source heterogeneous reviews:[J]. World Regional Studies, 2024, 33(10): 168-179.

和泽海, 陶玉国, 张红霞. 基于多源异构评论的旅游目的地形象及其影响因素[J]. 世界地理研究, 2024, 33(10): 168-179.

Figures/Tables 8

References 37

1	LAI K, LI X. Tourism destination image: Conceptual problems and definitional solutions. Journal of Travel Research,2016,55(8):1065-1080.
2	黄震方, 李想. 旅游目的地形象的认知与推广模式. 旅游学刊,2002,7(3):65-70.
	HUANG Z, LI X. On the image perception and promotion pattern of tourist destination. Tourism Tribune,2002,7(3):65-70.
3	陶玉国, 赵会勇, 李永乐. 基于结构方程模型的城市旅游形象影响因素测评. 人文地理,2010,25(6):125-130.
	TAO Y, ZHAO H, LI Y. Evaluation of factors affecting urban tourism image based on structural equation model. Human Geography,2010,25(6):125-130.
4	张宏梅, 陆林, 蔡利平, 等. 旅游目的地形象结构与游客行为意图——基于潜在消费者的本土化验证研究. 旅游科学,2011,25(1):35-45.
	ZHANG H, LU L, CAI L, et al. Tourism destination image structural model and visitors'behavioral intentions: based on a confirmatory study of localization of potential consumers, Tourism Sciences,2011,25(1):35-45.
5	HAUGLAND S A, NESS H, GRØNSETH B, et al. Development of tourism destinations: An integrated multilevel perspective[J]. Annals of Tourism Research,2011,38(1):268-290.
6	邴振华, 唐思琪, 王瑞静, 等. 基于地理标记照片的城市旅游意象空间分异研究——以五大世界著名旅游城市为例. 世界地理研究,2022,31(1):64-75.
	BING Z, TANG S, WANG R, et al. Exploring the spatial differentiation of urban tourism image based on geotagged photos-taking five world famous tourist cities as examples. World Regional Studies,2022,31(1):64-75.
7	HE Z, DENG N, LI X, et al. How to "read" a destination from images? machine learning and network methods for DMOs' image projection and photo evaluation. Journal of Travel Research,2022,61(3):597-619.
8	邱栋, 陈明礼. 数字平台生态系统驱动区域韧性发展的机理研究. 自然辩证法研究,2020,36(10):37-41.
	QIU D, CHEN M. Research on mechanism of digital platform ecosystem driving the development of regional resilience. Research on Dialectics of Nature,2020,36(10):37-41.
9	GONZALEZ-RODRIGUEZ M R, MARTINEZ-TORRES R, TORAL S. Post-visit and pre-visit tourist destination image through eWOM sentiment analysis and perceived helpfulness. International Journal of Contemporary Hospitality Management,2016,28(11):2609-2627.
10	陆利军, 廖小平. 基于UGC数据的南岳衡山旅游目的地形象感知研究. 经济地理,2019,39(12):221-229.
	LU L, LIAO X. Research on image perception of tourism destination based on UGC data: A case study of south mount heng. Economic Geography,2019,39(12):221-229.
11	LIU Y, HUANG K, BAO J, et al. Listen to the voices from home: An analysis of Chinese tourists' sentiments regarding Australian destinations. Tourism Management,2019,71:337-347.
12	XIANG Z, DU Q, MA Y, et al. A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management,2017,58(2),51–65.
13	TAO Y, LIU W, HUANG Z, et al. Thematic analysis of reviews on the air quality of tourist destinations from a sentiment analysis perspective. Tourism Management Perspectives,2022,42:100969.
14	BALOGLU S, MCCLEARY K W. A model of destination image formation. Annals of tourism research, 1999, 26(4): 868-897.
15	BEERLI A, MARTIN J D. Factors influencing destination image. Annals of Tourism Research,2004,33(3):657-681.
16	LAWTON L J. Resident perceptions of tourist attractions on the Gold Coast of Australia. Journal of Travel Research,2005,44(2):188-200.
17	LALICIC L, MARINE-ROIG E, FERRER-ROSELL B, et al. Destination image analytics for tourism design: An approach through airbnb reviews. Annals of Tourism Research,2021,86(1):103100.
18	QU H, KIM L H, IM H H. A model of destination branding: Integrating the concepts of the branding and destination image. Tourism Management,2011,32(3):465-476.
19	LEE S, SCOTT D, KIM H. Celebrity fan involvement and destination perceptions. Annals of Tourism Research,2008,35(3):809-832.
20	徐海军, 吕兴洋. 声音品牌化:目的地歌曲对旅游者感知形象的影响研究. 旅游科学,2019,33(6):1-16.
	XU H, LU X. Sonic branding:The effect of destination songs on tourists＇perceived image. Tourism Sciences,2019,33(6):1-16.
21	徐菲菲, 剌利青, Ye Feng. 基于网络数据文本分析的目的地形象维度分异研究——以南京为例. 资源科学,2018,40(7):1483-1493.
	XU F, LA L, YE F. Study on dimension differentiation of destination image based on text analysis of network data--taking Nanjing as an example. Resource Science,2018,40(7):1483-1493.
22	马小宾, 章锦河. 国外游客对世界文化遗产苏州园林的形象认知研究——基于自然语言处理的不同粒度分析. 中国生态旅游,2022,12(4):550-565.
	MA X, ZHANG J. A study on international tourists'perception of world cultural heritage suzhou garden's image: An application of different granularity analyses in natural language processing. China Ecotourism,2022,12(4):550-565.
23	徐戈,王厚峰. 自然语言处理中主题模型的发展. 计算机学报,2011,34(8):1423-1436.
	XU G, WANG H. The development of topic models in natural language processing. Journal of Computers,2011,34(8):1423-1436.
24	关鹏, 王曰芬. 基于LDA主题模型和生命周期理论的科学文献主题挖掘. 情报学报,2015,34(3):286-299.
	GUAN P, WANG Y. Topic mining in scientfic literature based on LDA topic model and life cycle theory. Journal of Information Science,2015.34(3):286-299.
25	周思敏. 游客口碑发布平台选择行为的影响因素研究. 北京:北京邮电大学,2021.
	ZHOU S. Research on the influencial factors of tourists'electronic word of mouth platform selection behavior. Beijing: Beijing University of Posts and Telecommunications,2021.
26	王晰巍, 邢云菲, 赵丹, 等. 基于社会网络分析的移动环境下网络舆情信息传播研究——以新浪微博"雾霾"话题为例. 图书情报工作,2015,59(7):14-22.
	WANG X, XING Y, ZHANO D, et al. The study of network public opinion dissemination with social network analysis under the mobile environment: A case of "Haze" in sina microblog. Library and Information Work,2015,59(7):14-22.
27	刘逸, 孟令坤, 保继刚,等. 人工计算模型与机器学习模型的情感捕捉效度比较研究——以旅游评论数据为例. 南开管理评论,2021,24(5):63-74.
	LIU Y, MENG L, BAO J, et al. A comparative study of sentiment computing methods: Will machine learning be overwhelming. Nankai Management Review,2021,24(5):63-74.
28	BLEI D M, NG A Y, JORDAN M I. Latent dirichlet allocation. Journal of Machine Learning Research,2003(3):993-1022.
29	CHEN X, LI J, HAN W, et al. Urban tourism destination image perception based on LDA integrating social network and emotion analysis: The example of Wuhan. Sustainability,2021,14(1):12.
30	陈绍辉, 王岩. 中国社会思潮研究的科学知识图谱分析——基于Citespace和Vosviewer的综合应用. 上海交通大学学报,2018,26(6):22-30.
	CHEN S, WANG Y. Analysis of scientific knowledge mapping in the study of Chinese social ideological trend: Comprehensive application based on citespace and VOSviewer.Journal of Shanghai Jiaotong University,2018,26(6): 22-30.
31	SU L, STEPCHENKOVA S, KIRILENKO A P. Online public response to a service failure incident: Implications for crisis communications. Tourism Management,2019,73:1-12.
32	饶梓欣, 李倩, 许鑫. 新冠肺炎疫情下公共图书馆视频内容生产与网络传播研究——以上海图书馆为例[J]. 图书馆杂志,2022,41(1):54-59.
	RAO Z, LI Q, XU X. Research on video content production and network communication in public library during COVID-19: A case study of Shanghai library. Library Journal,2022,41(1):54-59.
33	陈嘉钰, 李艳.基于LDA主题模型的社交媒体倦怠研究——以微信为例. 情报科学,2019,37(12):78-86.
	CHEN J, LI Y. Social Media Fatigue Research Based on LDA Topic Model——Take WeChat as An Example.Information Science,2019,37(12):78-86.
34	梁晨晨, 李仁杰. 综合LDA与特征维度的丽江古城意象感知分析. 地理科学进展,2020,39(4):614-626.
	LIANG C, LI R. Tourism destination image perception analysis based on the Latent Dirichlet Allocation model and dominant semantic dimensions: A case of the Old Town of Lijiang. Progress in Geographical Sciences,2020,39(4):614-626.
35	崔庆明, 和琳珊, 徐红罡. 遗产旅游动机的核心-边缘结构研究——以丽江为例. 旅游学刊,2016,31(10):84-93.
	CUI Q, HE L, XU H. The core-periphery structure of heritage tourism motivation in Lijiang. Tourism Journal,2016,31(10):84-93.
36	孙九霞, 王学基. 旅游目的地居民本土休闲文化与地方实践——以云南丽江为例. 广西民族大学学报(哲学社会科学版),2019,41(3):65-72.
	SUN J, WANG X. Local leisure culture and local practice of tourism destinations-A case study of Lijiang county. Journal of Guangxi University for Nationalities,2019,41(3):65-72.
37	LI J, DOU Z, ZHU Y, Zuo X, et al. Deep cross-platform product matching in e-commerce. Information Retrieval Journal,2020,23,136-158.

主题1: 历史文化		主题2：自然吸引物		主题3：社会氛围		主题4：夜生活和娱乐		主题5：餐饮服务		主题6：情感体验
四方街	0.010	雪山	0.003	朋友	0.005	摄影	0.004	推荐	0.003	喜欢	0.004
文化	0.009	樱花	0.003	生活	0.005	酒吧	0.004	阿勒邱	0.003	期待	0.003
博物馆	0.007	油菜花	0.002	女孩	0.003	打卡	0.004	米线	0.002	向往	0.002
纳西	0.004	花巷	0.002	音乐	0.002	徒步	0.003	好吃	0.002	智慧	0.002
历史	0.003	绿树	0.001	美好	0.002	咖啡	0.002	有名	0.002	自由	0.002
文明	0.003	美景	0.001	游客	0.002	逛逛	0.002	三文鱼	0.002	疫情	0.002
东巴	0.003	杜鹃花	0.001	孩子	0.002	民谣	0.002	酒店	0.002	矛盾	0.002
传统	0.002	生态	0.001	热闹	0.002	户外	0.002	美食	0.001	体验	0.002
古道	0.002	湖泊	0.001	主人	0.001	写真	0.002	土鸡	0.001	灿烂	0.002
纳西族	0.002	自然遗产	0.001	小朋友	0.001	自驾	0.001	排骨	0.001	值得	0.002

主题1: 历史文化		主题2：自然吸引物		主题3：社会氛围		主题4：夜生活和娱乐		主题5：餐饮服务		主题6：情感体验
四方街	0.010	雪山	0.003	朋友	0.005	摄影	0.004	推荐	0.003	喜欢	0.004
文化	0.009	樱花	0.003	生活	0.005	酒吧	0.004	阿勒邱	0.003	期待	0.003
博物馆	0.007	油菜花	0.002	女孩	0.003	打卡	0.004	米线	0.002	向往	0.002
纳西	0.004	花巷	0.002	音乐	0.002	徒步	0.003	好吃	0.002	智慧	0.002
历史	0.003	绿树	0.001	美好	0.002	咖啡	0.002	有名	0.002	自由	0.002
文明	0.003	美景	0.001	游客	0.002	逛逛	0.002	三文鱼	0.002	疫情	0.002
东巴	0.003	杜鹃花	0.001	孩子	0.002	民谣	0.002	酒店	0.002	矛盾	0.002
传统	0.002	生态	0.001	热闹	0.002	户外	0.002	美食	0.001	体验	0.002
古道	0.002	湖泊	0.001	主人	0.001	写真	0.002	土鸡	0.001	灿烂	0.002
纳西族	0.002	自然遗产	0.001	小朋友	0.001	自驾	0.001	排骨	0.001	值得	0.002

主题1: 景点标志物		主题2：夜生活和娱乐		主题3：经济价格		主题4：人物历史		主题5：情感体验		主题6：社会文化
大水车	0.01	酒吧	0.005	商业	0.014	徐霞客	0.013	值得	0.034	建筑	0.013
四方街	0.007	热闹	0.005	气息	0.011	古道	0.006	喜欢	0.024	文化	0.012
标志性	0.007	夜晚	0.004	性价比	0.007	外地人	0.004	推荐	0.009	特色	0.007
小桥流水	0.005	产品	0.004	商业化	0.007	木氏土司	0.004	好玩	0.006	纳西族	0.006
公园	0.004	打卡	0.004	店铺	0.003	游客	0.003	适合	0.005	文化遗产	0.006
标志	0.003	艳遇	0.003	免费	0.003	历史	0.002	很美	0.004	民族	0.005
核心	0.003	繁华	0.002	价格	0.002	热情	0.003	有趣	0.004	民居	0.005
木府	0.002	人头攒动	0.002	门票	0.002	老板	0.003	好吃	0.003	风格	0.004
五凤楼	0.002	安静	0.001	实惠	0.001	古街	0.002	很棒	0.002	传统	0.003
酒吧街	0.002	气氛	0.001	超市	0.002	朱元璋	0.001	舒服	0.002	东巴	0.002

主题1: 景点标志物		主题2：夜生活和娱乐		主题3：经济价格		主题4：人物历史		主题5：情感体验		主题6：社会文化
大水车	0.01	酒吧	0.005	商业	0.014	徐霞客	0.013	值得	0.034	建筑	0.013
四方街	0.007	热闹	0.005	气息	0.011	古道	0.006	喜欢	0.024	文化	0.012
标志性	0.007	夜晚	0.004	性价比	0.007	外地人	0.004	推荐	0.009	特色	0.007
小桥流水	0.005	产品	0.004	商业化	0.007	木氏土司	0.004	好玩	0.006	纳西族	0.006
公园	0.004	打卡	0.004	店铺	0.003	游客	0.003	适合	0.005	文化遗产	0.006
标志	0.003	艳遇	0.003	免费	0.003	历史	0.002	很美	0.004	民族	0.005
核心	0.003	繁华	0.002	价格	0.002	热情	0.003	有趣	0.004	民居	0.005
木府	0.002	人头攒动	0.002	门票	0.002	老板	0.003	好吃	0.003	风格	0.004
五凤楼	0.002	安静	0.001	实惠	0.001	古街	0.002	很棒	0.002	传统	0.003
酒吧街	0.002	气氛	0.001	超市	0.002	朱元璋	0.001	舒服	0.002	东巴	0.002

[1]	Wan HOU, Xiyong HOU, Min SUN, Baiyuan SONG. Land use/land cover change along low-middle latitude coastal areas of Eurasia and their driving forces from 2000 to 2010 [J]. World Regional Studies, 2021, 30(4): 813-825.
[2]	Lina WANG, Hua LI. Research into the negative perception of inbound tourists on the tourism destination image in China [J]. World Regional Studies, 2019, 28(6): 189-199.