不同来源地旅游者对北京目的地形象感知差异——基于深度学习的Flickr图片分析
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摘要
社交网络图片是旅游目的地形象传播的重要载体,基于图片表征内容的营销传播越来越受到旅游目的地营销组织重视,本文选取Flickr上中国港澳台(香港特别行政区、澳门特别行政区、台湾省)、英国和美国旅游者拍摄的北京图片作为研究素材,采用计算机深度学习算法分析图片表征内容,并从认知和情感2个层面分析、比较了不同来源地游客在北京旅游目的地形象感知方面的异同。研究表明,在认知形象方面,入境旅游者均对自然、建筑较为关注,但在文化艺术、人物、食物等具体维度上关注内容不尽相同。在情感形象方面,令人愉快(Pleasant)的、兴奋的(Exciting)是所有入境旅游者表现的主要情感,但中国港澳台和美国旅游者所拍摄图片隐含投射出困倦疲乏的(Sleepy)情感,而英国旅游者拍摄的图片则暗含不安苦恼(Distressing)的情感。本文利用计算机深度学习算法分析海量UGC图片表征内容为目的地形象研究提供了大数据的方法参考。
With the rapid development of the Internet, increasingly more tourists use social media to share travel experiences. User generated content(UGC) has become an important source of information for potential tourists, affecting their perception of tourism destination image(TDI) and tourism decision making. Photos, as one of the carrieres of UGC, is an important tool for the spread of TDI across cultures. However, most of the previous photo-based TDI research mainly adopt content or semantic analysis by human, and the number of samples analyzed was limited. When facing large-scale UGC photo collections, more automated analysis methods are needed to improve efficiency. This article introduces the deep learning theory of computer science into TDI for the first time, taking the pictures released by tourists(from Hong Kong, Macao, and Taiwan of China;the United States; the United Kingdom) as the research samples and using machine analysis from millions of destination related photos to represent content and construct the correspondence between destination cognitive and affective images. With regard to the cognitive image, inbound tourists are more concerned about nature and architecture, but they pay different attention to culture, art, people, food and other aspects. Tourists from Hong Kong, Macao, and Taiwan of China are mostly interested in cultural relics, entertainment activities, and food. UK tourists pay attention to facilities and urban environment. US tourists are more likely to photograph people. With regard to the affective image,"exciting"and"pleasant"are the most significant affective elements for inbound tourists. Hong Kong, Macao, Taiwan of China, and US tourists show some sign of sleepiness, and UK tourists show more sign of distress. According to these results, targeted marketing for the main inbound tourist source markets is needed. For tourists from Hong Kong,Macao, and Taiwan of China, it's essential to increase the cultural content of Beijing, diversify food and Beijing-style entertainment activities. For UK tourists, well-equipped facilities, diverse urban environments, and distinctive buildings are key marketing contents. Natural scenery and life of people are important symbols for attracting US tourists. In summary, this study used computer deep learning methods to analyze large-scale photo data sets, converting pictorial images into text to extract cognitive and affective images. It has both methodological and managerial implications.
With the rapid development of the Internet, increasingly more tourists use social media to share travel experiences. User generated content(UGC) has become an important source of information for potential tourists, affecting their perception of tourism destination image(TDI) and tourism decision making. Photos, as one of the carrieres of UGC, is an important tool for the spread of TDI across cultures. However, most of the previous photo-based TDI research mainly adopt content or semantic analysis by human, and the number of samples analyzed was limited. When facing large-scale UGC photo collections, more automated analysis methods are needed to improve efficiency. This article introduces the deep learning theory of computer science into TDI for the first time, taking the pictures released by tourists(from Hong Kong, Macao, and Taiwan of China;the United States; the United Kingdom) as the research samples and using machine analysis from millions of destination related photos to represent content and construct the correspondence between destination cognitive and affective images. With regard to the cognitive image, inbound tourists are more concerned about nature and architecture, but they pay different attention to culture, art, people, food and other aspects. Tourists from Hong Kong, Macao, and Taiwan of China are mostly interested in cultural relics, entertainment activities, and food. UK tourists pay attention to facilities and urban environment. US tourists are more likely to photograph people. With regard to the affective image,"exciting"and"pleasant"are the most significant affective elements for inbound tourists. Hong Kong, Macao, Taiwan of China, and US tourists show some sign of sleepiness, and UK tourists show more sign of distress. According to these results, targeted marketing for the main inbound tourist source markets is needed. For tourists from Hong Kong,Macao, and Taiwan of China, it's essential to increase the cultural content of Beijing, diversify food and Beijing-style entertainment activities. For UK tourists, well-equipped facilities, diverse urban environments, and distinctive buildings are key marketing contents. Natural scenery and life of people are important symbols for attracting US tourists. In summary, this study used computer deep learning methods to analyze large-scale photo data sets, converting pictorial images into text to extract cognitive and affective images. It has both methodological and managerial implications.
引文
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1）Flickr API 下载地址为https://github.com/alexis-mignon/python-flickr-api。
2）python官方网站为https://www.python.org/。
[2] Mackay K J, Fesenmaier D R. An exploration of cross-cultural des?tination image assessment[J]. Journal of Travel Research, 2000, 38(4):417-423.
[3]雷宇,张宏梅,徐菲菲,等.中国国家形象感知的跨文化比较:以中国、英国、美国大学生为例[J].旅游学刊, 2015, 30(3):23-34.[Lei Y, Zhang H M, Xu F F, et al. A cross-cultural comparison of Chinese country image perceptions:A case study of China, UK and USA university students[J]. Tourism Tribune, 2015, 30(3):23-34.]
[4]邓宁,钟栎娜,李宏.基于UGC图片元数据的目的地形象感知:以北京为例[J].旅游学刊, 2018, 33(1):53-62.[Deng N, Zhong L N, Li H. Perception of travel destination image based on user-gen?erated photograph metadata:The case of Beijing[J]. Tourism Tri?bune, 2018, 33(1):53-62.]
[5] Kim H, Richardson S L. Motion picture impacts on destination im?ages[J]. Annals of Tourism Research, 2003, 30(1):216-237.
[6] Chi G, Qu H. Examining the structural relationships of destination image, tourist satisfaction and destination loyalty:An integrated approach[J]. Tourism Management, 2008, 29(4):624-636.
[7] Stylidis D, Shani A, Belhassen Y. Testing an integrated destination image model across residents and tourists[J]. Tourism Manage?ment, 2017, 58:184-195.
[8]?nder I, Marchiori E. A comparison of pre-visit beliefs and pro?jected visual images of destinations[J]. Tourism Management Per?spectives, 2017, 21:42-53.
[9] Crompton J L. An assessment of the image of Mexico as a vacation destination and the influence of geographical location upon that image[J]. Journal of Travel Research, 1979, 17(4):18-23.
[10] Baloglu S, Mccleary K. A model of destination image formation[J].Annals of Tourism Research, 1999, 26(4):868-897.
[11] Beerli A, Mart?N?J D. Tourists’characteristics and the perceived image of tourist destinations:A quantitative analysis-a case study of Lanzarote, Spain[J]. Tourism Management, 2004, 25(5):623-636.
[12]李蕾蕾.旅游地形象的传播策略初探[J].深圳大学学报(人文社会科学版), 1999, 16(4):87-93.[Li L L. My first inquiry into the strategy of communicating the image of a tourist spot[J]. Journal of Shenzhen University(Humanities&Social Sciences), 1999, 16(4):87-93.]
[13]杨永德,白丽明.旅游目的地形象概念体系辨析[J].人文地理,2007,(5):94-98.[Yang Y D, Bai L M. Study on the conceptualiza?tion of tourist destination image[J]. Human Geography, 2007,(5):94-98.]
[14] Echtner C M, Ritchie J R B. The meaning and measurement of des?tination image[J]. Journal of Tourism Studies, 1991, 43:1-8.
[15] Hosany S, Ekinci Y, Uysal M. Destination image and destination personality:An application of branding theories to tourism places[J]. Journal of Business Research, 2006, 59(5):638-642.
[16] Molinillo S, Liébana-Cabanillas F, Anaya-Sánchez R, et al. DMO online platforms:Image and intention to visit[J]. Tourism Manage?ment, 2018, 65:116-130.
[17] Marine-Roig E, Ferrer-Rosell B. Measuring the gap between pro?jected and perceived destination images of Catalonia using compo?sitional analysis[J]. Tourism Management, 2018, 68:236-249.
[18] Phillips P, Barnes S, Zigan K, et al. Understanding the impact of online reviews on hotel performance[J]. Journal of Travel Research,2016, 56(2):235-249.
[19] Mischel W, Shoda Y. A cognitive-affective system theory of per?sonality[J]. Psychological Review, 1995, 102(2):246-268.
[20] Kim S E, Lee K Y, Shin S I, et al. Effects of tourism information quality in social media on destination image formation:The case of Sina Weibo[J]. Information Management, 2017, 54(6):687-702.
[21]杨永德,白丽明,苏振.旅游目的地形象的结构化与非结构化比较研究:以阳朔旅游形象测量分析为例[J].旅游学刊, 2007, 22(4):53-57.[Yang Y D, Bai L M, Su Z. A comparative study on the structured and unstructured measurements of tourist destination image:A case of Yangshuo, Guilin[J]. Tourism Tribune, 2007, 22(4):53-57.]
[22]郑荣娟,白凯,马耀峰.基于旅华美国游客手绘认知地图的中国旅游目的地意象研究[J].人文地理, 2014, 29(3):150-158.[Zheng R J, Bai K, Ma Y F. Research on the China destination im?age based on American tourists'sketch cognitive map[J]. Human Geography, 2014, 29(3):150-158.]
[23]张宏梅,陆林.入境旅游者旅游动机及其跨文化比较:以桂林、阳朔入境旅游者为例[J].地理学报, 2009, 64(8):989-998.[Zhang H M, Lu L. Cross-cultural research on inbound tourists’motivation:A case study of inbound tourists in Guilin and Yangshuo[J]. Acta Geographica Sinica, 2009, 64(8):989-998.]
[24] K?ltringer C, Dickinger A. Analyzing destination branding and im?age from online sources:A web content mining approach[J]. Jour?nal of Business Research, 2015, 68(9):1836-1843.
[25] Kim K Y, Jogaratnam G. Travel motivations:A comparative study of Asian international and domestic American college students[J].Journal of Travel Tourism Marketing, 2002, 13(4):61-82.
[26] Stepchenkova S K, Kim H, Kirilenko A. Cultural differences in pictorial destination images:Russia through the camera lenses of American and Korean tourists[J]. Journal of Travel Research,2015, 54(6):1219-1223.
[27] Andreu L, Enrique BignéJ, Cooper C. Projected and perceived im?age of Spain as a tourist destination for British travellers[J]. Jour?nal of Travel&Tourism Marketing, 2000, 9(4):47-67.
[28] Lo I S, McKercher B, Lo A, et al. Tourism and online photography[J]. Tourism Management, 2011, 32(4):725-731.
[29]吴茂英,沈海莉.新媒体时代视觉材料与目的地形象关系研究[J].旅游学刊, 2018, 33(3):5-7.[Wu M L, Shen H L. Research on the relationship between visual Materials and destination image in the new media age[J]. Tourism Tribune, 2018, 33(3):5-7.]
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1）Flickr API 下载地址为https://github.com/alexis-mignon/python-flickr-api。
2）python官方网站为https://www.python.org/。