PROJECT TITLE :

egoSlider: Visual Analysis of Egocentric Network Evolution

ABSTRACT:

Ego-network, which represents relationships between a particular individual, i.e., the ego, and people connected to it, i.e., alters, is a essential target to check in Social Network Analysis. Evolutionary patterns of ego-networks along time give huge insights to several domains like sociology, anthropology, and psychology. But, the analysis of dynamic ego-networks remains difficult because of its difficult time-varying graph structures, for example: alters come back and leave, ties grow stronger and fade away, and alter communities merge and split. Most of the existing dynamic graph visualization techniques mainly focus on topological changes of the whole network, which is not adequate for egocentric analytical tasks. In this paper, we gift egoSlider, a visual analysis system for exploring and comparing dynamic ego-networks. egoSlider provides a holistic image of the information through multiple interactively coordinated views, revealing ego-network evolutionary patterns at 3 totally different layers: a macroscopic level for summarizing the whole ego-network knowledge, a mesoscopic level for overviewing specific individuals' ego-network evolutions, and a microscopic level for displaying detailed temporal info of egos and their alters. We demonstrate the effectiveness of egoSlider with a usage state of affairs with the DBLP publication records. Conjointly, a controlled user study indicates that normally egoSlider outperforms a baseline visualization of dynamic networks for finishing egocentric analytical tasks.