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Encyclopedia of Social Network Analysis and Mining 2014

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Encyclopedia of Social Network Analysis and Mining

Previous Figure Next Figure. Such active participation has caught the attention of many research groups that are focusing on understanding human behavior to study the dynamics of these social networks.

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Oftentimes, perceiving these networks is hard, mainly due to either the large size of the data involved or the ineffective use of visualization strategies. This work introduces VizTract to ease the visual perception of complex social networks. VizTract is a two-level graph abstraction visualization tool that is designed to visualize both hierarchical and adjacency information in a tree structure.

On this data, social groups are referred to as circles, social network users as nodes , and interactions as edges between the nodes. Our approach is to present a visual overview that represents the interactions between circles, then let the user navigate this overview and select the nodes in the circles to obtain more information on demand. VizTract aim to reduce visual clutter without any loss of information during visualization. VizTract enhances the visual perception of complex social networks to help better understand the dynamics of the network structure.

VizTract within a single frame, not only reduces the complexity but also avoids redundancy of the nodes and the rendering time. The visualization techniques used in VizTract are the force-directed layout, circle packing, cluster dendrogram, and hierarchical edge bundling.

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Furthermore, to enhance the visual information perception, VizTract provides interaction techniques such as selection, path highlight, mouse-hover, and bundling strength. This method helps social network researchers to display large networks in a visually effective way that is, conducive to ease interpretation and analysis.

We conduct a study to evaluate the user experience of the system and then collect information about their perception via a survey. The goal of the study is to know how humans can interpret the network when visualized using different visualization methods. Our results indicate that users heavily prefer those visualization techniques that aggregate the information and the connectivity within a given space, such as hierarchical edge bundling.

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Read Edit History Discussions. Visualization of complex social networks Created by: Ramya Akula. Big Data Cogn. Table of Content [ Hide ]. It is one of the most prominent questions answered through this work. One way is to represent the data hierarchically in a single frame. It not only reduces the complexity but also avoids redundancy of the nodes.

This also helps the user to save his time by avoiding scrolling up, down, sideways to see the whole network.

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Social Networks - Encyclopedia of Social Work

Don't have an account? Sign in via your Institution. Sign in with your library card. Search within Show Summary Details Abstract and Keywords Social networks are structures composed of relational patterns of interactions among a set of actors. Kirk A.