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An Analysis on the Trend of Weibo‘Follow’Patterns of University Libraries Based on Association Rules
Received date: 2014-03-24
Revised date: 2014-04-08
Online published: 2014-04-20
This paper introduces two different processes of Weibo data acquisition: the API based acquisition and Python based acquisition. The association rules are implemented to analyze the Weibo's‘follow’data of certain university libraries. It also proposes levels of the‘follow'hierarchy in Weibo. Then we use association rules to describe‘1st level’and‘2nd level’follow regulations. We discovered an ultimate pattern or characteristic of Weibo's transmission is formed through constantly passing‘follow’to one another. University libraries can use methods presented in this paper to make prospective survey on their Weibo development.
Key words: association rules; university library; Weibo; follow
Cheng Xiufeng , Li Chongyang , Chen Liyue . An Analysis on the Trend of Weibo‘Follow’Patterns of University Libraries Based on Association Rules[J]. Library and Information Service, 2014 , 58(08) : 73 -78 . DOI: 10.13266/j.issn.0252-3116.2014.08.012
[1] 郑娟, 祝宁. 基于信息传播模式的微博信息挖掘与应用[J]. 新闻世界, 2011(5): 91-92.
[2] 新浪发布.中国微博元年市场白皮书[EB/OL].[2013-12-26].http://ishare.iask.sina.com.cn/f/14220084.html.
[3] 廉捷,周欣,曹伟,等.新浪微博数据挖掘方案[J].清华大学学报(自然科学版),2011,51(10): 1300-1305.
[4] 齐鹏,李隐峰,宋玉伟. 基于Python的Web数据采集技术[J].电子科技,2012,25(11): 118-120.
[5] 唐琼,袁媛,刘钊. 我国高校图书馆微博服务现状调查研究——以新浪认证用户为例[J].大学图书馆学报,2013(3):97-103.
[6] 朱玉全, 孙志挥. 快速更新频繁项集[J].计算机研究与发展,2003,40(1):94-99.
[7] Agrawal R, Mannila H, Srikant R, et al. Fast discovery of association rules[J]. Advances in Knowledge Discovery and Data Mining,1996,12(1): 307-328.
[8] 颜跃进, 李舟军, 陈火旺. 频繁项集挖掘算法[J]. 计算机科学,2004,31(3):112-114.
[9] Wasito I, Sadikin M, Handhayani T. Predictive genotype based on phenotype using the association rules mining[C]//Advanced Computer Science and Information Systems (ICACSIS). 2013 International Conference on. IEEE, 2013: 185-188.
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