Assessment of personal environments in social networks

被引：0
|
作者：
Kolonin, Anton [1 ]
机构：
[1] Aigents Grp, Novosibirsk, Russia
来源：
2017 SIBERIAN SYMPOSIUM ON DATA SCIENCE AND ENGINEERING (SSDSE) | 2017年
关键词：
data science; machine learning; personal data; social engineering; social network; text mining;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper justifies importance of study of personal social environments in social networks, suggests practical metrics for its assessment, describes web application developed for this purpose and evaluates its practical applicability in different social networks.
引用
收藏
页码：61 / 64
页数：4
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