The Empirical Study of h-Degree in Recommendation Network of Academic Blogs——Taking ScienceNet.cn Blogs as an Example
Tan Min1, Xu Xin2
1 Department of Information Resource Management, Zhejiang University, Hangzhou 310027, China;
2 Department of Information Science, Business School, East China Normal University, Shanghai 200241, China
[Objective] This paper studies the features of h-degree in recommendation network of academic blogs. [Methods] Based on the datasets of blogs in ScienceNet.cn in 2013, construct the recommendation network of academic blogs, calculate the h-degree and related measures, and enter discussion by information visualization. [Results] In recommendation network of academic blogs, the generation of nodes with high h-degree is not only caused by academic knowledge connotations which are held by the information source (bloggers), but also because of the interest from topic the information source provided. This paper explores an approximate functional relationship (NA=b×hA2) between h-degree (hA) and node weighted degree (NA). Nodes with high h-degree typically become the organizer of subgroup in the center of a network. [Limitations] H-degree is not a perfect indicator, and the future studies will expand the improved h-degree. [Conclusions] H-degree can be one of the measurements for recommendation network analysis of academic blogs, and h-degree is also important for community management of this kind community.
谭旻, 许鑫. 学术博客推荐网络的h度实证——以科学网博客为例[J]. 现代图书情报技术, 2015, 31(7-8): 31-36.
Tan Min, Xu Xin. The Empirical Study of h-Degree in Recommendation Network of Academic Blogs——Taking ScienceNet.cn Blogs as an Example. New Technology of Library and Information Service, 2015, 31(7-8): 31-36.
[1] Otte E, Rousseau R. Social Network Analysis: A Powerful Strategy, also for the Information Sciences [J]. Journal of Information Science, 2002, 28(6): 441-453.
[2] Borner K, Sanyal S, Vespignani A. Network Science [J]. Annual Review of Information Science and Technology, 2007, 41: 537-607.
[3] Zhao S X, Rousseau R, Ye F Y. H-Degree as a Basic Measure in Weighted Networks [J]. Journal of Informetrics, 2011, 5(4): 668-677.
[4] Schubert A. A Hirsch-type Index of Co-author Partnership Ability [J]. Scientometrics, 2012, 91(1): 303-308.
[5] Rousseau R. Comments on "A Hirsch-type Index of Co-author Partnership Ability" [J]. Scientometrics, 2012, 91(1): 309-310.
[6] Yan X B, Zhai L, Fan W. C-index: A Weighted Network Node Centrality Measure for Collaboration Competence [J]. Journal of Informetrics, 2013, 7(1): 223-239.
[7] Abbasi A. H-Type Hybrid Centrality Measures for Weighted Networks [J]. Scientometrics, 2013, 96(2): 633-640.
[8] Zhai L, Yan X B, Zhang G. A Centrality Measure for Communication Ability in Weighted Network [J]. Physica A-Statistical Mechanics and Its Applications, 2013, 392(23): 6107-6117.
[9] 刘玮. 电子商务系统中的信息推荐方法研究[J]. 情报科学, 2006, 24(2): 300-303. (Liu Wei. Research on Information Recommendation in E-commerce Systems [J]. Information Science, 2006, 24(2): 300-303.)
[10] 胡昌平, 胡吉明, 邓胜利. 基于社会化群体作用的信息聚合服务[J]. 中国图书馆学报, 2010, 36(3): 51-56. (Hu Changping, Hu Jiming, Deng Shengli. Information Aggregation Service Based on the Role of Socialization Groups [J]. Journal of Library Science in China, 2010, 36(3): 51-56.)
[11] Hirsch J E. An Index to Quantify an Individual's Scientific Research Output [J]. Proceedings of the National Academy of Sciences of the United States of America, 2005, 102(46): 16569-16572.
[12] Zhao S X, Ye F Y. Exploring the Directed H-degree in Directed Weighted Networks [J]. Journal of Informetrics, 2012, 6(4): 619-630.
[13] 徐孝娟, 赵宇翔, 朱庆华. 民族志决策树方法在学术博客用户行为中的研究——以科学网博客为例[J]. 现代图书情报技术, 2014(1): 79-86. (Xu Xiaojuan, Zhao Yuxiang, Zhu Qinghua. Explore User's Behavior of Academic Blog Based on EDTM: Take Blog. Sciencenet as an Example [J]. New Technology of Library and Information Service, 2014(1): 79-86.)
[14] 周春雷, 朱向林. 科学网图情博客发展现状研究[J]. 图书情报知识, 2013(5): 98-105. (Zhou Chunlei, Zhu Xianglin. Study on LIS Blogs in Science Net [J]. Document, Informaiton & Knowledge, 2013(5): 98-105.)
[15] Egghe L. Power Laws in the Information Production Process: Lotkaian Informetrics [M]. Elsevier Academic Press, 2005.
