NodeTrix: a Hybrid Visualization of Social Networks

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Towards Better Analysis of Deep Convolutional Neural Networks (2016, methodology): “Inspired by NodeTrix [19], we allow experts to drag a neuron out of a neuron cluster or to another neuron cluster.”
Hierarchical Aggregation for Information Visualization: Overview, Techniques, and Design Guidelines (2010, methodology): “The NodeTrix [46] technique combines node-link diagrams with adjacency matrices for representing communities in social networks.”
Data-intensive applications, challenges, techniques and technologies: A survey on Big Data (2014, background): “SNA include social system design [204], human behavior modeling [95], social network visualization [127,164], social networks evolution analysis [27], and graph query and mining [111].”
A Taxonomy and Survey of Dynamic Graph Visualization (2017, background): “While not all combinations are sensible, there are a number of hybrid variants that appear to be promising: for instance, the combination of node-link diagrams and matrices have already been successfully explored for static graphs [HF07, HFM07].”
An Interactive Node-Link Visualization of Convolutional Neural Networks (2015, background): “, [15,24]), the edges of CNNs can be implied by their regular pattern.”