Egocentric Analysis of Dynamic Networks with EgoLines | Zendy

Jian Zhao | Zendy; Michael Glueck | Zendy; Fanny Chevalier | Zendy; Yanhong Wu | Zendy; Azam Khan | Zendy

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Egocentric Analysis of Dynamic Networks with EgoLines

Author(s) -

Jian Zhao,

Michael Glueck,

Fanny Chevalier,

Yanhong Wu,

Azam Khan

Publication year - 2016

Publication title -

hal (le centre pour la communication scientifique directe)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.1145/2858036.2858488

Subject(s) - subnetwork , computer science , social network analysis , metaphor , intelligence analysis , human–computer interaction , trace (psycholinguistics) , visualization , set (abstract data type) , domain (mathematical analysis) , visual analytics , network analysis , data science , dynamic network analysis , data visualization , artificial intelligence , world wide web , mathematical analysis , computer network , linguistics , philosophy , physics , computer security , mathematics , quantum mechanics , social media , programming language

International audienceThe egocentric analysis of dynamic networks focuses on discovering the temporal patterns of a subnetwork around a specific central actor (i.e., an ego-network). These types of analyses are useful in many application domains, such as social science and business intelligence, providing insights about how the central actor interacts with the outside world. We present EgoLines, an interactive visualization to support the egocentric analysis of dynamic networks. Using a "subway map" metaphor, a user can trace an individual actor over the evolution of the ego-network. The design of EgoLines is grounded in a set of key analytical questions pertinent to egocentric analysis, derived from our interviews with three domain experts and general network analysis tasks. We demonstrate the effectiveness of EgoLines in egocentric analysis tasks through a controlled experiment with 18 participants and a use-case developed with a domain expert

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