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Conference Paper/Proceeding/Abstract 325 views 52 downloads

Dynamic Network Plaid / Alexandra Lee; Daniel Archambault; Miguel Nacenta

CHI '19 Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Pages: 1 - 14

Swansea University Author: Daniel, Archambault

DOI (Published version): 10.1145/3290605.3300360

Abstract

Network data that changes over time can be very useful for studying a wide range of important phenomena, from how social network connections change to epidemiology. However, it is challenging to analyze, especially if it has many actors, connections or if the covered timespan is large with rapidly c...

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Published in: CHI '19 Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
ISBN: 978-1-4503-5970-2
Published: Glasgow CHI Glasgow 2019 2019
URI: https://cronfa.swan.ac.uk/Record/cronfa48160
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Abstract: Network data that changes over time can be very useful for studying a wide range of important phenomena, from how social network connections change to epidemiology. However, it is challenging to analyze, especially if it has many actors, connections or if the covered timespan is large with rapidly changing links (e.g., months of changes with changes at second resolution). In these analyses one would often like to compare many periods of time to others, without having to look at the full timeline. To support this kind of analysis we designed and implemented a technique and system to visualize this dynamic data. The Dynamic Network Plaid (DNP) is designed for large displays and based on user-generated interactive timeslicing on the dynamic graph attributes and on linked provenance-preserving representations. We present the technique, interface and the design/evaluation with a group of public health researchers investigating non-suicidal self-harm picture sharing in Instagram.
College: College of Science
Start Page: 1
End Page: 14