DİNLE

MSc.Thesis Defense:Hasan Alp Boz11-07-2019

A Visual Multivariate Dynamic EgoCentric

Network Exploration Tool

 

 

Hasan Alp Boz
Computer Science & Engineering
, MSc. Thesis, 2019

 

Thesis Jury

Assoc. Prof. Selim Balcısoy(Thesis Advisor), Prof. Dr. Burçin Bozkaya, Asst. Prof. Günce  Orman (Galatasaray University)

 

 

Date & Time: July 18th, 2019 –  3.00 PM

Place:  FENS 2019

Keywords : Exploratory Visual Analysis, Multivariate Dynamic Networks, Egocentric Analysis

 

Abstract

 

Visualizing multivariate dynamic networks is a challenging task. The evolution of the dynamic network within the temporal axis must be depicted in conjunction with the associated multivariate attributes. In this thesis, an exploratory visual analytics tool is proposed to display multivariate dynamic networks with spatial attributes. The proposed tool displays the distribution of multivariate temporal domain and network attributes in scattered views. Moreover, in order to expose the evolution of a single or a group of nodes in the dynamic network along the temporal axis, an egocentric approach is applied in which a node is represented with its neighborhood as an ego-network. This approach allows users to observe a node's surrounding environment along the temporal axis. On top of the traditional ego-network visualization methods, such as timelines, the proposed tool encodes ego-networks as feature vectors consisting of the domain and network attributes and projects them onto 2D views. As a result, distances between projected ego-networks represent the dissimilarity across temporal axis in a single view. The proposed tool is demonstrated with a real-world use case scenario on merchant networks obtained from a one-year long credit card transactions.