Please wait a minute...
New Technology of Library and Information Service  2016, Vol. 32 Issue (6): 54-62    DOI: 10.11925/infotech.1003-3513.2016.06.07
Orginal Article Current Issue | Archive | Adv Search |
Analyzing Food Community with Recipes and Weibo User Reviews
Wu Xiaolan1,2,Zhang Chengzhi2,3()
1School of Management Science and Engineering, Anhui University of Finance and Economics, Bengbu 233030, China
2Department of Information Management, Nanjing University of Science and Technology, Nanjing 210094, China
3Jiangsu Key Laboratory of Data Engineering and Knowledge Service, Nanjing 210093, China
Download: PDF(2041 KB)   HTML ( 44
Export: BibTeX | EndNote (RIS)      
Abstract  

[Objective] This study examines the structure of online food community with the help of large-scale real world data. [Methods] First, we collected recipes from meishij.net (a popular food network online) and user reviews from Sina Weibo (micro-blog) respectively. Second, we identified the Weibo users who mentioned recipes from meishij.net and mapped them to provinces and cuisines coordinate systems. Finally, we used community discovery algorithm to analyze the food community’s structure. [Results] The province and cuisines networks showed clear community structures. [Limitations] Demographic disparity might pose some effects to the conclusions. [Conclusions] The tastes of consumers from different provinces could be classified as “freshly salty”, “hot and spicy”, as well as “others”. “Sichuan” or “Yungui” dishes are rarely ordered together, while “Jing”, “Hu”, “Lu” and “Dongbei” dishes are often ordered along with each other. Besides, the regional cuisines have some geographical proximity among themselves.

Key wordsFood culture      Regional cuisines      Food community      Web information organization     
Received: 17 March 2016      Published: 18 July 2016

Cite this article:

Wu Xiaolan,Zhang Chengzhi. Analyzing Food Community with Recipes and Weibo User Reviews. New Technology of Library and Information Service, 2016, 32(6): 54-62.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2016.06.07     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2016/V32/I6/54

[1] 陈国林. 饮食文化学: 研究概述与学科距离[J]. 四川烹饪高等专科学校学报, 2013(2): 4-7.
[1] (Chen Guolin.Study of Food Culture: An Overiew and Its Constraints[J]. Journal of Sichuan Higher Institute of Cuisine, 2013(2): 4-7.)
[2] Wagner C, Singer P, Strohmaier M. The Nature and Evolution of Online Food Preferences [J]. EPJ Data Science, 2014, 3(1): Article No. 38.
[3] Ahn Y Y, Ahnert S.The Flavor Network[J]. Leonardo, 2013, 46(3): 272-273.
[4] 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.
[5] Ahn Y Y, Ahnert S E, Bagrow J P, et al.Flavor Network and the Principles of Food Pairing [OL]. arXiv: 1111.6074.
[6] Abbar S, Mejova Y, Weber I. You Tweet What You Eat: Studying Food Consumption Through Twitter [OL]. arXiv Preprint, 2014. arXiv: 14124361.
[7] Girvan M, Newman M E.Community Structure in Social and Biological Networks[J]. Proceedings of the National Academy of Sciences, 2002, 99(12): 7821-7826.
[8] Newman M E, Girvan M.Finding and Evaluating Community Structure in Networks[J]. Physical Review E, 2004, 69(2): 026113.
[9] Shi J, Malik J.Normalized Cuts and Image Segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(8): 888-905.
[10] Von Luxburg U.A Tutorial on Spectral Clustering[J]. Statistics and Computing, 2007, 17(4): 395-416.
[11] Raghavan U N, Albert R, Kumara S.Near Linear Time Algorithm to Detect Community Structures in Large-scale Networks[J]. Physical Review E, 2007, 76(3): 036106.
[12] Zhu X, Ghahramani Z.Learning from Labeled and Unlabeled Data with Label Propagation[R]. Carnegie Mellon University, 2002. .
[13] Zachary W W.An Information Flow Model for Conflict and Fission in Small Groups[J]. Journal of Anthropological Research, 1977, 33(4): 452-473.
[14] Newman M E.Analysis of Weighted Networks[J]. Physical Review E, 2004, 70(5): 056131.
[15] 宋玉蓉, 蒋国平, 徐加刚. 一种基于元胞自动机的自适应网络病毒传播模型[J]. 物理学报, 2011, 60(12): 110-119.
[15] (Song Yurong, Jiang Guoping, Xu Jiagang.An Epidemic Spreading Model in Adaptive Networks Based on Cellular Automata[J]. Acta Physica Sinica, 2011, 60(12): 110-119.)
[16] 吴亮, 朱士群. 网络中的节点权重及其物理意义[C]. 见: 第十二届全国量子光学学术会议论文摘要集. 2006.
[16] (Wu Liang, Zhu Shiqun.Node Weights and Its Physical Significance in Netwroks [C]. In: Proceedings of the 12th National Symposium on Quantum Optics. 2006.)
No related articles found!
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn