@inproceedings{400e461ecf894f309986b1bcbf99d291,
title = "Evaluating Perceptually Complementary Views for Network Exploration Tasks",
abstract = "We explore the relative merits of matrix, node-link and combined side-by-side views for the visualisation of weighted networks with three controlled studies: (1) finding the most effective visual encoding for weighted edges in matrix representations; (2) comparing matrix, node-link and combined views for static weighted networks; and (3) comparing MatrixWave, Sankey and combined views of both for event-sequence data. Our studies underline that node-link and matrix views are suited to different analysis tasks. For the combined view, our studies show that there is a perceptually complementary effect in terms of improved accuracy for some tasks, but that there is a cost in terms of longer completion time than the faster of the two techniques alone. Eye-movement data shows that for many tasks participants strongly favour one of the two views, after trying both in the training phase.",
keywords = "Event sequence data, Eye tracking, Matrices, Network visualisation, Node-link diagrams, Sankey diagrams",
author = "Chunlei Chang and Benjamin Bach and Tim Dwyer and Kim Marriott",
year = "2017",
month = may,
day = "2",
doi = "10.1145/3025453.3026024",
language = "English",
volume = "2017-May",
series = "CHI '17",
publisher = "Association for Computing Machinery, Inc",
pages = "1397--1407",
booktitle = "Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems",
note = "2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017 ; Conference date: 06-05-2017 Through 11-05-2017",
}