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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (11): 84-93    DOI: 10.11925/infotech.2096-3467.2017.0782
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Studying Dietary Preferences of Chinese Residents
Yue Zijing, Zhang Chengzhi(), Zhou Qingqing
School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China
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Abstract  

[Objective] This study investigates the dietary preferences of Chinese users from different regions to reveal the differences of dietary culture among them, and then provides suggestion to the catering industry. [Context] It took researchers long period of time to collect small amount of data of dietary preferences. With the development of social media, we could retrieve large-scale dietary information more effectively. [Methods] We collected user-generated content (UGC) from Dianping.com to explore their dietary preferences. [Results] Users’ dietary preferences were very different in the developed regions. Meanwhile, there was significant negative correlation between geographic distances and the similarities of users’ dietary preferences. Finally, users paid more attention to the taste, service and environment of the restaurants. [Conclusions] Research based on the user-generated content can reflect their dietary preferences and reveal the differences of dietary cultures.
Key words： Social Computing      Preference Mining      User Generated Content      Dietary Preferences      Dietary Aspects     
Received: 05 August 2017      Published: 27 November 2017
ZTFLH:  G203  
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Zijing Yue
Chengzhi Zhang
Qingqing Zhou

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Yue Zijing,Zhang Chengzhi,Zhou Qingqing. Studying Dietary Preferences of Chinese Residents. Data Analysis and Knowledge Discovery, 2017, 1(11): 84-93.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.0782     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I11/84

商户ID 用户ID 用户注册地 评论时间 评论内容
50**2 2**2 上海 2003/7/10 牛肉拉面还是蛮好吃的, 现在又增加了凉粉也不错。
57**7 2**8 山东 2005/12/20 过桥米线比较正宗的一家店。店面不大, 服务差点。
18**0 5**0 上海 2014/9/21 大众消费, 拉条子挺好, 烤肉正宗, 吃羊肉串这儿放心。
序号 地区 菜肴偏好分布熵 序号 地区 菜肴偏好分布熵
1 香港 8.540 18 重庆 7.939
2 上海 8.413 19 河南 7.916
3 广东 8.388 20 安徽 7.887
4 北京 8.259 21 陕西 7.790
5 福建 8.221 22 贵州 7.761
6 浙江 8.176 23 广西 7.743
7 澳门 8.110 24 辽宁 7.668
8 四川 8.110 25 河北 7.635
9 江苏 8.080 26 山西 7.563
10 江西 8.075 27 黑龙江 7.495
11 海南 8.062 28 内蒙古 7.454
12 山东 8.052 29 甘肃 7.388
13 云南 8.049 30 吉林 7.342
14 天津 8.048 31 新疆 7.143
15 湖北 8.032 32 宁夏 7.048
16 湖南 7.995 33 西藏 6.940
17 台湾 7.967 34 青海 6.689
序号 地区名 地区名 饮食偏好
相似度		 序号 地区名 地区名 饮食偏好
相似度
1 江苏 上海 0.579 6 广东 澳门 0.500
2 江苏 浙江 0.569 7 北京 河北 0.493
3 浙江 上海 0.518 8 江苏 安徽 0.482
4 香港 上海 0.515 9 四川 重庆 0.477
5 贵州 云南 0.505 10 广东 香港 0.464
各地区间的
地理距离		 各地区间的
饮食相似度
各地区间的地理距离 1 -.508**
各地区间的饮食相似度 -.508** 1
饮食属性 属性词集
味道 味道、味道儿、口味、口味儿、口感
环境 环境、氛围、装潢、气氛
服务 服务、服务态度、态度、服务员、服务生、店员
价格 价格、价钱、菜价、价位、价额、单价、定价
份量 份量、量、分量、菜量、菜份量
[1] Mintz S W, Bois C M D. The Anthropology of Food and Eating[J]. Annual Review of Anthropology, 2002, 31(1): 99-119.
doi: 10.2307/4132873
[2] Civitello L.Cuisine and Culture: A History of Food and People[M]. New York: John Wiley & Sons, 2011.
[3] Allhoff F, Monroe D.Food & Philosophy: Eat, Think, and Be Merry[M]. New York: Wiley-Blackwell, 2007.
[4] Cantarero L, Espeitx E, Gil Lacruz M, et al.Human Food Preferences and Cultural Identity: The Case of Aragón (Spain)[J]. International Journal of Psychology, 2013, 48(5): 881-890.
doi: 10.1080/00207594.2012.692792 pmid: 22916705
[5] 杨君, 邱杰, 胡安福, 等. 吸烟人群饮食习惯引起的吸烟(烟气)偏好分析[J]. 科技通报, 2014, 30(9): 42-46.
[5] (Yang Jun, Qiu Jie, Hu Anfu, et al.Smoking (Mainstream Smoke) Preference Caused by Dietary Habit in Chinese Cigarette Smokers[J]. Bulletin of Science and Technology, 2014,30(9): 42-46.)
[6] 寿小婧, 邢燕, 韩济生, 等. 孤独症儿童饮食谱及食物偏好研究[J]. 中华行为医学与脑科学杂志, 2014, 23(5): 413-415.
doi: 10.3760/cma.j.issn.1674-6554.2014.05.009
[6] (Shou Xiaojing, Xing Yan, Han Jisheng, et al.The Food Repertoire and Food Preference in Children with Autism Spectrum Disorder[J]. Chinese Journal of Behavioral Medicine and Brain Science, 2014, 23(5): 413-415.)
doi: 10.3760/cma.j.issn.1674-6554.2014.05.009
[7] 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[J]. 图书情报工作, 2015, 59(7):14-22.
doi: 10.13266/j.issn.0252-3116.2015.07.002
[7] (Wang Xiwei, Xing Yunfei, Zhao Dan, et al.The Study of Network Public Opinion Dissemination with Social Network Analysis Under the Mobile Environment: A Case of “Haze” in Sina Micro-blog[J]. Library and Information Service, 2015, 59(7): 14-22.)
doi: 10.13266/j.issn.0252-3116.2015.07.002
[8] 张瑜, 李兵, 刘晨玥. 面向主题的微博热门话题舆情监测研究——以“北京单双号限行常态化”舆情分析为例[J]. 中文信息学报, 2015, 29(5): 143-151.
doi: 10.3969/j.issn.1003-0077.2015.05.019
[8] (Zhang Yu, Li Bing, Liu Chenyue.Research on Topic-oriented Supervision of Public Sentiment Towards Heated Weibo Events ——A Case Study of “Implementing 'Odd-Even' Vehicle Restriction on a Regular Basis”[J]. Journal of Chinese Information Processing, 2015, 29(5): 143-151.)
doi: 10.3969/j.issn.1003-0077.2015.05.019
[9] 李君. 基于在线评论的个性化推荐系统[D]. 成都: 电子科技大学, 2013.
[9] (Li Jun.Personalized Recommendation System Based on Online Reviews[D]. Chengdu: University of Electronic Science and Technology of China, 2013.)
[10] 颛悦, 熊锦华, 程学旗. 一种融合个性化与多样性的人物标签推荐方法[J]. 中文信息学报, 2017, 31(2): 154-162.
[10] (Zhuan Yue, Xiong Jinhua, Cheng Xueqi.User Tag Recommendation with Personalization and Diversity[J]. Journal of Chinese Information Processing, 2017, 31(2): 154-162.)
[11] 傅向华, 刘国, 郭岩岩, 等. 中文博客多方面话题情感分析研究[J]. 中文信息学报, 2013, 27(1): 47-55.
doi: 10.3969/j.issn.1003-0077.2013.01.007
[11] (Fu Xianghua, Liu Guo, Guo Yanyan, et al.Multi-aspect Topic Sentiment Analysis of Chinese Blog[J]. Journal of Chinese Information Processing, 2013, 27(1): 47-55.)
doi: 10.3969/j.issn.1003-0077.2013.01.007
[12] Settanni M, Marengo D.Sharing Feelings Online: Studying Emotional Well-being via Automated Text Analysis of Facebook Posts[J]. Frontiers in Psychology, 2015, 6:1045. DOI: 10.3389/fpsyg.2015.01045.
doi: 10.3389/fpsyg.2015.01045 pmid: 4512028
[13] Chung W, Zeng D.Social-Media-based Public Policy Informatics: Sentiment and Network Analyses of U.S. Immigration and Border Security[J]. Journal of the Association for Information Science and Technology, 2016, 67(7): 1588-1606.
doi: 10.1002/asi.23449
[14] Barreda A, Bilgihan A.An Analysis of User-Generated Content for Hotel Experiences[J]. Journal of Hospitality and Tourism Technology, 2013, 4(3): 263-280.
doi: 10.1108/JHTT-01-2013-0001
[15] 杨志墨. 基于社区发现的移动自媒体用户兴趣建模[D]. 西安: 西安电子科技大学, 2015.
[15] (Yang Zhimo.User Interest Modeling for Mobile We Media Based on Community Discovery[D]. Xi’an: Xidian University, 2015.)
[16] 赵华, 章成志. 利用作者主题模型进行图书馆UGC的主题发现与演化研究[J]. 图书馆论坛, 2016, 36(7): 34-45.
[16] (Zhao Hua, Zhang Chengzhi.Topic Detection and Evolution of Library User Generated Content Based on Author-Topic Model[J]. Library Tribune, 2016,36(7): 34-45.)
[17] 张晓勇, 周清清, 章成志. 面向在线社交网络用户生成内容的饮食话题发现研究[J]. 现代图书情报技术, 2016(10): 70-80.
[17] (Zhang Xiaoyong, Zhou Qingqing, Zhang Chengzhi.Identifying Food Topics from User-Generated Contents in Microblogs[J]. New Technology of Library and Information Service, 2016(10): 70-80.)
[18] Li Y, Jiang J, Liu T.Inferring User Consumption Preferences from Social Media[J]. IEICE Transactions on Information and Systems, 2017, 100(3): 537-545.
doi: 10.1587/transinf.2016EDP7265
[19] Vollmer R L, Baietto J.Practices and Preferences: Exploring the Relationships Between Food-related Parenting Practices and Child Food Preferences for High Fat and/or Sugar Foods, Fruits, and Vegetables[J]. Appetite, 2017, 113: 134-140.
doi: 10.1016/j.appet.2017.02.019 pmid: 28235620
[20] 任彬, 车万翔, 刘挺. 基于依存句法分析的社会媒体文本挖掘方法——以饮食习惯特色分析为例[J]. 中文信息学报, 2014, 28(6): 208-215.
[20] (Ren Bin, Che Wanxiang, Liu Ting.Dependency Parsing-Based Social Media Text Mining ——A Case Study in Analysis of Weibo Users’ Eating Habits[J]. Journal of Chinese Information Processing, 2014, 28(6): 208-215.)
[21] 任彬. 基于微博的用户饮食特色及表达习惯分析[D]. 哈尔滨: 哈尔滨工业大学, 2015.
[21] (Ren Bin.Analysis of Diet Habits and Diet Expression Habits Based on Microblog[D]. Harbin: Harbin Institute of Technology, 2015.)
[22] Zhu Y X, Huang J, Zhang Z K, et al.Geography and Similarity of Regional Cuisines in China[J]. PLoS One, 2013, 8(11): e79161.
doi: 10.1371/journal.pone.0079161 pmid: 3832477
[23] Vidal L, Ares G, Machín L, et al.Using Twitter Data for Food-related Consumer Research: A Case Study on “What People Say When Tweeting about Different Eating Situations”[J]. Food Quality & Preference, 2015, 45:58-69.
doi: 10.1016/j.foodqual.2015.05.006
[24] Abbar S, Mejova Y, Weber I.You Tweet What You Eat: Studying Food Consumption Through Twitter[C]// Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2015: 3197-3206.
[25] 岳子静, 章成志, 周清清. 利用在线评论挖掘用户饮食偏好——以北京地区为例[J]. 图书馆论坛, 2017, 37(3): 108-115.
[25] (Yue Zijing, Zhang Chengzhi, Zhou Qingqing.Mining User Diet Preference with Online Reviews——A Case Study of Beijing City[J]. Library Tribune, 2017, 37(3): 108-115.)
[26] Mood A M, Graybill F A, Boes D C.Introduction to the Theory of Statistics[M]. The 3rd Edition. New York: McGraw-Hill, 1974.
[27] 唐晓波, 梁梦婕. 融合结构与内容特征的微博沉默用户兴趣模型构建研究[J]. 情报学报, 2015, 34(11): 1214-1224.
doi: 10.3772/j.issn.1000-0135.2015.011.010
[27] (Tang Xiaobo, Liang Mengjie.Research of Silent User Interest Modeling in Microblog Based on the Features of Structure and Content[J]. Journal of the China Society for Scientific and Technical Information, 2015, 34(11): 1214-1224.)
doi: 10.3772/j.issn.1000-0135.2015.011.010
[28] Chang J S.Domain Specific Word Extraction from Hierarchical Web Documents: A First Step Toward Building Lexicon Trees from Web Corpora[C]//Proceedings of the 4th SIGHAN Workshop on Chinese Language Processing. Stroudsburg, PA, USA: ACL, 2005: 64-71.
[29] Salton G, Wong A, Yang C S.A Vector Space Model for Automatic Indexing[J]. Communications of the ACM, 1975, 18(11): 613-620.
doi: 10.1145/361219.361220
[30] Salton G, Buckley C.Term-weighting Approaches in Automatic Text Retrieval[J]. Information Processing & Management, 1988, 24(5): 513-523.
doi: 10.1016/0306-4573(88)90021-0
[31] 李纲, 李岚凤, 毛进, 等. 作者合著网络中研究兴趣相似性实证研究[J]. 图书情报工作, 2015,59(2):75-81.
doi: 10.13266/j.issn.0252-3116.2015.02.012
[31] (Li Gang, Li Lanfeng, Mao Jin, et al.Empircal Research on Similarity of Research Interests in Co-authorship Network[J]. Library and Information Service, 2015,59(2): 75-81.)
doi: 10.13266/j.issn.0252-3116.2015.02.012
[32] 黄宏程, 陆卫金, 胡敏, 等. 用户兴趣相似性度量的关系预测算法[J]. 计算机科学与探索, 2017,11(7): 1068-1079.
doi: 10.3778/j.issn.1673-9418.1606038
[32] (Huang Hongcheng, Lu Weijin, Hu Min, et al.User Relationships Prediction Algorithm with Interest Similarity Measurement[J]. Journal of Frontiers of Computer Science and Technology, 2017, 11(7): 1068-1079.)
doi: 10.3778/j.issn.1673-9418.1606038
[33] Tan P N, Steinbach M, Kumar V.Introduction to Data Mining[M]. Addison-Wesley, 2005.
[34] Hu M, Liu B.Mining and Summarizing Customer Reviews[C]//Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2004: 168-177.
[35] 陈茂榕. 领域依赖的Web信息抽取系统设计与实现[D]. 南京: 东南大学, 2016.
[35] (Chen Maorong.The Design and Implementation of Domain Dependent Web Information Extraction System[D]. Nanjing: Southeast University, 2016.)
[36] 韦强申. 领域关键词抽取:结合LDA与Word2Vec[D]. 贵阳: 贵州师范大学, 2016.
[36] (Wei Qiangshen.Keyword Extraction Based on LDA and Word2Vec[D]. Guiyang: Guizhou Normal University, 2016.)
[37] Hinton G E.Learning Distributed Representations of Concepts[C]//Proceedings of the 8th Annual Conference of the Cognitive Science Society. Hillsdale, NJ: Erlbaum, 1986: 1-12.
[38] Tobler W R.A Computer Movie Simulating Urban Growth in the Detroit Region[J]. Economic Geography, 1970, 46(S1): 234-240.
doi: 10.2307/143141
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