# DyEgoVis: Visual Exploration of Dynamic Ego-Network Evolution
## 3 Task Analysis  
A dynamic network \(G\) is modeled as a graph sequence \(G=\{G^{1},G^{2},\ldots,G^{T}\}\) where \(T\) is total number of timesteps and the timespan is represented as [1, T]. The network snapshot \(G^{t}\) at timestep \(t\) is a static graph \(G^{t}=\{V^{t},E^{t},A^{t}\}\) where \(V^{t}\) is a node set, \(E^{t}\) is edge set and \(A^{t}\) is a set of node attributes. The node set \(V\) of \(G\) is the union of the snapshots' node sets and the edge set \(E\) of \(G\) is the union of the snapshots' edge sets. In \(G\), the dynamic ego-network of each node \(u\in V\) is represented as an ego-network sequence \(G(u)=\{G^{1}_{u},G^{2}_{u},\ldots,G^{t}_{u}\}\) where \(G^{t}_{u}=\{V^{t}_{u},E^{t}_{u},A^{t}\}\) is the ego-network snapshot of the ego \(u\) at timestep \(t\). Analytical tasks play a key role in designing a visualization system. However, few studies offer comprehensive analytical tasks that guide users to explore dynamic ego-networks from multiple analysis levels. [PERSON] et al. [4] proposed analytical tasks at three levels: a macro-level for overviewing all dynamic ego-networks, a meso-level for summarizing the specified dynamic ego-networks' evolutions, and a micro-level for showing temporal ego-alter relationships. However, they do not consider how to help users quickly find dynamic ego-networks with similar or abnormal evolution patterns. [PERSON] et al. [2] mainly focused on micro-level tasks for analyzing the evolution of a dynamic ego-network. [PERSON] et al. [36] handled analytical tasks at the global, subgroup and node/link levels. Unfortunately, they also do not consider the above question. [PERSON] et al. [38] addressed macro-level tasks but did not fully consider local-level and individual-level tasks. Based on the existing analytical tasks [39] and the visual information seeking mantra 'overview, zoom and filter, details-on-demand' [6], we summarize the analytical tasks at the three analysis levels. Global-level tasks. At this analysis level, we aim to summarize the evolutions of all dynamic ego-networks in a dynamic network. The tasks are as follows:  
T1: Get the whole picture of dynamic ego-networks' evolution patterns in an overview view. Through this view, users can understand the overall evolution patterns of dynamic ego-networks and find similar or abnormal dynamic ego-networks. T2: Explore the distributions of dynamic ego-networks along the timeline. Are there similar or abnormal states (snapshots) at each timestep? Are there any clusters? If so, how do these clusters evolve over time? Do they merge, split or disappear? T3: Analyze the evolutions of all dynamic ego-networks in the specified timespan. During this timespan, how do dynamic ego-networks evolve? Which dynamic ego-networks have similar evolution patterns? Local-level tasks. At this analysis level, we focus on comparing and analyzing the evolutions of the selected dynamic ego-networks. The tasks are as follows:  
T4: Summarize all evolution states of the selected dynamic ego-networks in an overview view. From this view, users can quickly find similar or abnormal states without having to inspect them one by one along the timeline. T5: Compare and analyze changes in the properties of the selected dynamic ego-networks. How do their properties change over time? Do they increase, decrease or keep stable?Individual-level tasks. At this analysis level, we visualize the selected dynamic ego-networks and explore the changes in ego-alter relationships. The tasks are as follows:  
T6: Visualize the overall structure of each dynamic ego-network. How should each snapshot be laid out to allow users to track and analyze one-level and two-level alters? T7: Analyze changes in the number of alters. How does the number of one- or two-level alters evolve? Do they increase, decrease or remain? Are there any peaks or valleys? If so, what are the causes? T8: Investigate the specified alter. How long is its lifespan? When does it appear, disappear and reappear? How long does it appear consecutively? How long does it disappear?