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现代图书情报技术  2016, Vol. 32 Issue (6): 54-62     https://doi.org/10.11925/infotech.1003-3513.2016.06.07
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
基于菜谱与微博用户评论的饮食社区挖掘研究*
吴小兰1,2,章成志2,3()
1安徽财经大学管理科学与工程学院 蚌埠 233030
2南京理工大学信息管理系 南京 210094
3江苏省数据工程与知识服务重点实验室 南京 210093
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
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摘要 

目的】以大规模真实社交网络数据作支撑研究饮食社区结构。【方法】使用“美食杰”网站的菜谱信息和新浪微博上与菜有关的微博数据, 完成用户与菜之间的“提及”关系构建后, 分别在省份地区维度和地区菜系维度进行映射, 并运用社区发现算法进行社区挖掘。【结果】在省份地区关系网和地区菜系关系网上存在明显的社区结构。【局限】实验过程中发达地区人数与边缘地区人数悬殊太大, 对本文所得结论有一定的影响。【结论】实证结果发现: 省份地区被划分成“其他口味”、“鲜咸味”、“香辣味”三个口味地区; “川菜”、“云贵菜”因辅料独特很少与其他菜系被一起点餐, “京菜”、“沪菜”、“鲁菜”、“东北菜”常被一起点餐, 除此之外, 地区菜系之间存在一定程度的地理位置近邻性。

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吴小兰
章成志
关键词 饮食文化地方菜系饮食社区Web信息组织    
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
收稿日期: 2016-03-17      出版日期: 2016-07-18
基金资助:*本文系国家社会科学基金项目“在线社交网络中基于用户的知识组织模式研究”(项目编号:14BTQ033)、安徽省教育厅人文社会科学项目“基于社交网络的交叉学科知识发现及其应用研究”(项目编号:SK2016A0025)和江苏省数据工程与知识服务重点实验室开放课题“在线社交网络上交叉学科用户知识结构发现及其兴趣演变研究”(项目编号:DEKS2014KT006)的研究成果之一
引用本文:   
吴小兰,章成志. 基于菜谱与微博用户评论的饮食社区挖掘研究*[J]. 现代图书情报技术, 2016, 32(6): 54-62.
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.
链接本文:  
https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2016.06.07      或      https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2016/V32/I6/54
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