Visual Interactive Approach for Mining Twitter’s Networks

Authors

Y. Abdelsadek , K. Chelghoum, F. Herrmann, I. Kacem, and B. Otjacques

Reference

Data Mining and Big Data (ISBN 978-3-319-40972-6), vol. 9714 of the series Lecture Notes in Computer Science, pp. 342-349, 2016

Description

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.

Link

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