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Book Section Year : 2016

Visual Interactive Approach for Mining Twitter’s Networks

Abstract

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.
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hal-04000603 , version 1 (22-02-2023)

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Youcef Abdelsadek, Kamel Chelghoum, Francine Herrmann, Imed Kacem, Benoît Otjacques. Visual Interactive Approach for Mining Twitter’s Networks. Data Mining and Big Data, 9714, Springer International Publishing, pp.342-349, 2016, Lecture Notes in Computer Science, ⟨10.1007/978-3-319-40973-3_34⟩. ⟨hal-04000603⟩
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