Analysis of Spatial Interaction between Different Food Cultures in South and North China: Practices from People’s Daily Life
Abstract
:1. Introduction
2. Study Area and Data Description
3. Methodology
3.1. Text Preprocessing
3.2. Spatial Interaction Patterns among Different Cultures
3.2.1. Place Name Relation Inference
3.2.2. Classification of Hot Cultural Topics
- (1)
- Sampling is performed on the Dirichlet distribution, whose hyperparameter is α, to generate topic distribution of document .
- (2)
- The following three operations are performed for each word in . First, sampling is performed on multinomial distribution , representing topics, to generate its corresponding topic . Second, sampling is performed on the Dirichlet distribution, whose hyperparameter is , to generate topic ’s corresponding to word distribution . Third, sampling is performed on multinomial distribution , representing words, to generate word .
3.2.3. Emotion Analysis
4. Results
4.1. Spatial Distribution Patterns of Cultural Interactions between North and South
4.2. Hotspot Cultural Topics
4.3. Analysis of Emotional Characteristics Based on Cultural Food Differences between North and South
5. Discussion and Conclusion
5.1. Discussion
5.1.1. Fuzziness of Place Name Symbols
5.1.2. Precision of Semantic Parsing
5.1.3. Influence of Personal Attributes of the Sample Data on Analysis Results
5.2. Conclusion and Future Direction
Author Contributions
Funding
Conflicts of Interest
References
- Lopez, J.J.R. The symbolic appropriated territory, an updated tradition in the new cultural geography. Rev. Geogr. Venez. 2018, 59, 434–447. [Google Scholar]
- Cresswell, T. New cultural geography-an unfinished project? Cult. Geogr. 2010, 17, 169–174. [Google Scholar] [CrossRef]
- Jackson, P. New directions in cultural geography revisited. Area 2016, 48, 367–370. [Google Scholar] [CrossRef]
- Cresswell, T.; Mitchell, D. Cultural Geography: A Critical Introduction. Econ. Geogr. 2002, 34, 334–339. [Google Scholar] [CrossRef]
- Goheen, P.G. Cultural geography: A critical introduction. Ann. Assoc. Am. Geogr. 2001, 91, 572–573. [Google Scholar]
- Brazeau, R. The cultural geography of revolution. Ir. Stud. Rev. 2019, 27, 442–446. [Google Scholar] [CrossRef]
- Peach, C. Social geography: New religions and ethnoburbs—Contrasts with cultural geography. Prog. Hum. Geog. 2002, 26, 252–260. [Google Scholar] [CrossRef] [Green Version]
- Cook, I. A new vocabulary for cultural-economic geography? Dialogues Hum. Geogr. 2019, 9, 83–87. [Google Scholar] [CrossRef]
- Zimmerer, K.S. Cultural ecology: At the interface with political ecology—The new geographies of environmental conservation and globalization. Prog. Hum. Geog. 2006, 30, 63–78. [Google Scholar] [CrossRef]
- Steinbrink, M.; Aufenvenne, P. On othering and mainstreamisation of new cultural geography. Some scientometric observations. Mitt. Osterr. Geogr. G 2017, 159, 83–104. [Google Scholar]
- Turan, Y.; Cekic, A. Coping with loneliness: Loneliness, religious coping, religiosity, life satisfaction and social media usage. Cumhur. Ilah. Derg. 2018, 22, 1711–1745. [Google Scholar]
- Orben, A.; Dienlin, T.; Przybylski, A.K. Social media’s enduring effect on adolescent life satisfaction. Proc. Natl. Acad. Sci. USA 2019, 116, 10226–10228. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Andrade, C.S.; Santos, M.Y. Sentiment analysis with text mining in contexts of big data. Int. J. Technol. Hum. Interact. 2017, 13, 47–67. [Google Scholar] [CrossRef]
- Naji, M.; Daoudi, N.; Ajhoun, R. Spatio-Temporal Context for Improving Sentiment Analysis Accuracy. In Proceedings of the 2018 6th International Conference on Multimedia Computing and Systems (ICMCS), Rabat, Morocco, 10–12 May 2018; pp. 390–395. [Google Scholar]
- Majumder, N.; Hazarika, D.; Gelbukh, A.; Cambria, E.; Poria, S. Multimodal sentiment analysis using hierarchical fusion with context modeling. Knowl. Based Syst. 2018, 161, 124–133. [Google Scholar] [CrossRef] [Green Version]
- Chera, M. Food culture: Anthropology, linguistics, and food studies. Soc. Anthropol. 2018, 26, 579–581. [Google Scholar] [CrossRef]
- Tolia-Kelly, D.P. The geographies of cultural geography III: Material geographies, vibrant matters and risking surface geographies. Prog. Hum. Geogr. 2013, 37, 153–160. [Google Scholar] [CrossRef] [Green Version]
- Edvardsson, B.; Enquist, B.; Johnston, R. Co-creating customer value through hyperreality in the prepurchase service experience. J. Serv. Res. 2005, 8, 149–161. [Google Scholar] [CrossRef]
- Kandra, S.; Ghosh, M. Environmental perception: Image based analysis of people’s impression of places. Int. J. Appl. Environ. Sci. 2017, 12, 1223–1239. [Google Scholar]
- Mirnig, N.; Strasser, E.; Weiss, A.; Tscheligi, M. Studies in Public Places as a Means to Positively Influence People’s Attitude towards Robots; International Conference on Social Robotics; Springer: Heidelberg, Germany, 2012; pp. 209–218. [Google Scholar]
- Portugali, J. On the relations between cognitive maps and images of cities. Cogn. Process. 2018, 19, S6. [Google Scholar]
- Boulding, K.E. The image: Knowledge in life and society. J. Political Econ. 1957, 54, 112–113. [Google Scholar]
- Reynolds, W.H. The role of the consumer in image building. Calif. Manag. Rev. 1965, 7, 69–76. [Google Scholar] [CrossRef]
- Filomena, G.; Verstegen, J.A.; Manley, E. A computational approach to the image of the city. Cities 2019, 89, 14–25. [Google Scholar] [CrossRef]
- Chapman, E.H.; Lynch, K. The Image of the City. J. Aesthet. Art Crit. 1962, 11, 46–68. [Google Scholar]
- Guo, C.C. The important relationship between environment design and city image. In Proceedings of the 2018 7th International Conference on Social Science, Education and Humanities Research, Sanya, China, 25–27 November 2018; pp. 31–34. [Google Scholar]
- Oshimi, D.; Harada, M. Host residents’ role in sporting events: The city image perspective. Sport Manag. Rev. 2019, 22, 263–275. [Google Scholar] [CrossRef]
- Li, J.J.; Lu, Y. Chinese culture in tourist research: A review and comparison of Chinese and English studies in 1993–2012. Tour. Rev. 2016, 71, 118–134. [Google Scholar] [CrossRef]
- Wong, I.A.; McKercher, B.; Li, X.P. East meets west: Tourist interest in hybrid culture at postcolonial destinations. J. Travel Res. 2016, 55, 628–642. [Google Scholar] [CrossRef]
- Beriault, M.; Laurier, C.; Guay, J.P. Allegiance to gang culture: The role of ethnic identity among young offenders in the montreal area. Criminologie 2017, 50, 287–310. [Google Scholar]
- Oh, D.E.S. Social life in social media. Fudan J. Hum. Soc. Sci. 2018, 11, 119–122. [Google Scholar] [CrossRef]
- Hawi, N.S.; Samaha, M. The relations among social media addiction, self-esteem, and life satisfaction in university students. Soc. Sci. Comput. Rev. 2017, 35, 576–586. [Google Scholar] [CrossRef]
- Ly, T.; Pamer, C.; Dang, O.; Brajovic, S.; Haider, S.; Botsis, T.; Milward, D.; Winter, A.; Lu, S.; Ball, R. Evaluation of natural language processing (NLP) systems to annotate drug product labeling with meddra terminology. J. Biomed. Inform. 2018, 83, 73–86. [Google Scholar] [CrossRef]
- Moreno, D.C.; Vargas-Lombardo, M. Design and construction of an NLP based knowledge extraction methodology in the medical domain applied to clinical information. Healthc. Inform. Res. 2018, 24, 376–380. [Google Scholar] [CrossRef]
- Purks, J.L.; Harris, M.; Anderson, K.E.; Shoulson, I. Natural language processing (NLP) of verbatim consequence patient-reported outcomes highlight functional ability as important to patients. Neurotherapeutics 2018, 15, 1192. [Google Scholar]
- Xu, G.X.; Meng, Y.T.; Qiu, X.Y.; Yu, Z.H.; Wu, X. Sentiment analysis of comment texts based on bilstm. IEEE Access 2019, 7, 51522–51532. [Google Scholar] [CrossRef]
- Basiri, M.E.; Ghasem-Aghaee, N.; Naghsh-Nilchi, A.R. Exploiting reviewers’ comment histories for sentiment analysis. J. Inf. Sci. 2014, 40, 313–328. [Google Scholar] [CrossRef]
- Liu, L.Z.; Liu, H.; Wang, H.S.; Song, W.; Lu, J.L. The study of sentiment analysis on Chinese comment texts. In Proceedings of the 2014 5th IEEE International Conference on Software Engineering and Service Science (Icsess), Beijing, China, 27–29 June 2014; pp. 397–401. [Google Scholar]
- Qi, W.; Liu, S.H.; Zhao, M.F.; Liu, Z. China’s different spatial patterns of population growth based on the hu line. J. Geogr. Sci. 2016, 26, 1611–1625. [Google Scholar] [CrossRef]
- Wang, F.H.; Liu, C.L.; Xu, Y.P. Analyzing population density disparity in china with GIS-automated regionalization: The hu line revisited. Chin. Geogr. Sci. 2019, 29, 541–552. [Google Scholar] [CrossRef] [Green Version]
- Chen, M.X.; Gong, Y.H.; Li, Y.; Lu, D.D.; Zhang, H. Population distribution and urbanization on both sides of the hu Huanyong line: Answering the premier’s question. J. Geogr. Sci. 2016, 26, 1593–1610. [Google Scholar] [CrossRef]
- Hu, Z.C.; Wang, Y.L.; Liu, Y.S.; Long, H.L.; Peng, J. Spatio-temporal patterns of urban-rural development and transformation in east of the hu Huanyong line, china. ISPRS Int. J. Geo-Inf. 2016, 5, 24. [Google Scholar] [CrossRef] [Green Version]
- Li, X.D.; Zhang, C. Research on enhancing the effectiveness of the Chinese text automatic categorization based on ictclas segmentation method. In Proceedings of the 2013 IEEE 4th International Conference on Software Engineering and Service Science, Beijing, China, 23–25 May 2012; pp. 267–270. [Google Scholar]
- Tajbakhsh, M.S.; Bagherzadeh, J. Semantic knowledge LDA with topic vector for recommending hashtags: Twitter use case. Intell. Data Anal. 2019, 23, 609–622. [Google Scholar] [CrossRef]
- Zhang, Y.L.; Eick, C.F. Tracking events in twitter by combining an LDA-based approach and a density-contour clustering approach. Int. J. Semant. Comput. 2019, 13, 87–110. [Google Scholar] [CrossRef]
- Stevens, K.; Kegelmeyer, P.; Andrzejewski, D.; Buttler, D. Exploring Topic Coherence over Many Models and Many Topics. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, Jeju Island, Korea, 12–14 July 2012; pp. 952–961. [Google Scholar]
- Mimno, D.M.; Wallach, H.M.; Talley, E.M.; Leenders, M.; Mccallum, A. Optimizing Semantic Coherence in Topic Models. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, Edinburgh, UK, 27–31 July 2011; pp. 262–272. [Google Scholar]
- Min, K.R.; Ma, C.G.; Zhao, T.M.; Li, H.Y. Bosonnlp: An ensemble approach for word segmentation and pos tagging. In Natural Language Processing and Chinese Computing; Springer: Cham, Switzerland, 2015; Volume 9362, pp. 520–526. [Google Scholar]
- Hong, W.; Su, Y.S. The effect of institutional proximity in non-local university-industry collaborations: An analysis based on Chinese patent data. Res. Policy 2013, 42, 454–464. [Google Scholar] [CrossRef]
- Fisch, C.O.; Block, J.H.; Sandner, P.G. Chinese university patents: Quantity, quality, and the role of subsidy programs. J. Technol. Transfer. 2016, 41, 60–84. [Google Scholar] [CrossRef]
- Huntington, S.P. The Clash of Civilizations: And the Remaking of World Order. Financ. Dev.-Engl. Ed. 1998, 25, 158–162. [Google Scholar]
Steps | Results |
---|---|
Zhihu text | I’m from Guangdong. What struck me most when I lived in Heilongjiang was that when I passed a food street while hanging out with a friend from North …. |
Place name extraction | Guangdong, Heilongjiang, and the North |
Place name analysis | This text contains three place name information, in which only one belongs to the South. Based on the semantics, the place name is a place of origin. The remaining two names related to the North are in an inclusion relation (North > Heilongjiang) and, based on semantics, belong to places of destination. Therefore, according to the principle of accuracy, the place name in the text can be determined as Guangdong, Heilongjiang. Based on the direct preposition “from” between Guangdong and Heilongjiang, we can infer that the Cantonese is headed to Heilongjiang. |
Final result | (Guangdong → Heilongjiang) |
Steps | Result |
---|---|
Zhihu text | I’m from Harbin, before I went to Beijing for university, I have never been out of my hometown, which has limited my experience. However, wherever I go, I am used to local food. For example, I had noodles for several days in Xi’an, and I’m still thinking of the noodles that I had at a stall in midnight. When I went to Xiamen for the first time, I exclaimed how delicious was the seafood even for me, who barely had any seafood for 20 years. |
Place name extraction | Harbin, Beijing, Xi’an, and Xiamen |
Place name analysis | The text contains four place names, in which only one is a place of origin. The remaining three names are in a parallel relation and belong to places of destination. Therefore, we can infer that this text is about a Harbin person’s comment on the food of the other three cities. |
Final result | (Harbin → Beijing), (Harbin → Xi’an), and (Harbin → Xiamen) |
Category ID | Topics | Example | Number of Topical Words | Ratio |
---|---|---|---|---|
1 | location | canteen, dormitory, home | 6085 | 5.65% |
2 | geography object | mountain, sea, Yangtze River | 177 | 0.16% |
3 | place name | Nanjing, Shandong, Suzhou | 27,084 | 8.10% |
4 | animal | cockroach, snake, gecko | 1450 | 1.35% |
5 | dialect | Cantonese, Rhotic accent, accent | 2966 | 2.76% |
6 | costume | jacket, short sleeve, shirt | 1907 | 1.77% |
7 | climate | winter, ultracold, muggy | 6063 | 5.63% |
8 | emotion | like, disgusting, can not stand | 6297 | 5.85% |
9 | body characteristics | stomach, skin, mouth | 1354 | 1.26% |
10 | human figure | fair complexion, tall, fat | 534 | 0.50% |
11 | living habit | bath, clean, laundry | 6474 | 6.01% |
12 | living goods | toothbrush, window, heating | 3072 | 2.85% |
13 | time | spring festival, summer vacation | 4373 | 4.06% |
14 | food | hot pot, rice, noodles | 39,548 | 36.74% |
15 | plants | flower, grass, tree | 257 | 0.24% |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Zhang, H.; Zhou, X.; Huang, Y. Analysis of Spatial Interaction between Different Food Cultures in South and North China: Practices from People’s Daily Life. ISPRS Int. J. Geo-Inf. 2020, 9, 68. https://doi.org/10.3390/ijgi9020068
Zhang H, Zhou X, Huang Y. Analysis of Spatial Interaction between Different Food Cultures in South and North China: Practices from People’s Daily Life. ISPRS International Journal of Geo-Information. 2020; 9(2):68. https://doi.org/10.3390/ijgi9020068
Chicago/Turabian StyleZhang, Haiping, Xingxing Zhou, and Yi Huang. 2020. "Analysis of Spatial Interaction between Different Food Cultures in South and North China: Practices from People’s Daily Life" ISPRS International Journal of Geo-Information 9, no. 2: 68. https://doi.org/10.3390/ijgi9020068