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LOOM: Showing the Dynamics of Power Laws in Twitter Data
Author(s)
Date Issued
2017-07-14
Date Available
2017-11-29T10:39:20Z
Abstract
LOOM is advanced as a new visualisation for changes in ranks and trends in power-law data that is changing dynamically over time. A comparison between LOOM and existing methods for visualising such data (e.g.,time-series graphs, typical analytics dashboards). Several exemplar data sets are shown, using LOOM, drawn from the tracking of news stories on Twitter. The basis for the LOOM visualisation is elaborated and it is shown how it avoids the pitfalls arising in other line-graph representations.
Sponsorship
Science Foundation Ireland
Other Sponsorship
Insight Centre
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2017 IEEE
Language
English
Status of Item
Peer reviewed
Journal
Information Visualisation (IV), 2017 21st International Conference
Conference Details
21st International Conference on Information Visualisation (iV2017) London South Bank University, London, United Kingdom, 11-14 July 2017
This item is made available under a Creative Commons License
File(s)
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Name
insight_publication.pdf
Size
962 KB
Format
Adobe PDF
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