Discovering Motifs in Real-World Social Networks

被引：0
|
作者：
Romijn, Lotte [1 ]
Nuallain, Breanndan O. [1 ,2 ]
Torenvliet, Leen [2 ]
机构：
[1] Amsterdam Univ Coll, Amsterdam, Netherlands
[2] Univ Amsterdam, ILLC, NL-1012 WX Amsterdam, Netherlands
来源：
SOFSEM 2015: THEORY AND PRACTICE OF COMPUTER SCIENCE | 2015年 / 8939卷
关键词：
approximate counting; software development; social networks; big data; GRAPHS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We built a framework for analyzing the contents of large social networks, based on the approximate counting technique developed by Gonen and Shavitt. Our toolbox was used on data from a large forum-boards. ie-the most prominent community website in Ireland. For the purpose of this experiment, we were granted access to 10 years of forum data. This is the first time the approximate counting technique is tested on real-world, social network data.
引用
收藏
页码：463 / 474
页数：12
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