Visual Interactive Approach for Mining Twitter's Networks

被引：1

作者：

Abdelsadek, Youcef ^{[1
]}

Chelghoum, Kamel ^{[1
]}

Herrmann, Francine ^{[1
]}

Kacem, Imed ^{[1
]}

Otjacques, Benoit ^{[2
]}

机构：

[1] Univ Lorraine, LCOMS, EA 7306, Metz, France

[2] Luxembourg Inst Sci & Technol, E Sci Res Unit, Environm Res & Innovat Dept, Belvaux, Luxembourg

来源：

DATA MINING AND BIG DATA, DMBD 2016 | 2016年 / 9714卷

关键词：

Graph visualization; Interactive visualization; Community detection; Twitter's networks; SOCIAL NETWORKS;

D O I：

10.1007/978-3-319-40973-3_34

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Understanding the semantic behind relational data is very challenging, especially, when it is tricky to provide efficient analysis at scale. Furthermore, the complexity is also driven by the dynamical nature of data. Indeed, the analysis given at a specific time point becomes unsustainable even incorrect over time. In this paper, we rely on a visual interactive approach to handle Twitter's networks using NLCOMS. NLCOMS provides multiple and coordinated views in order to grasp the underlying information. Finally, the applicability of the proposed approach is assessed on real-world data of the ANR-Info-RSN project.

引用

页码：342 / 349

页数：8

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