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Identifying Root Cause and Derived Effects in Causal Relationships
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. University of Skövde . (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0002-2415-7243
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. University of Skövde. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0001-6245-5850
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. University of Skövde. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0003-2900-9335
2017 (English)In: Human Interface and the Management of Information: Information, Knowledge and Interaction Design: 19th International Conference, HCI International 2017, Vancouver, BC, Canada, July 9–14, 2017, Proceedings, Part I / [ed] Sakae Yamamoto, Springer, 2017, p. 22-34Conference paper, Published paper (Refereed)
Abstract [en]

This paper focuses on identifying factors that influence the process of finding a root cause and a derived effect in causal node-link graphs with associated strength and significance depictions. We discuss in detail the factors that seem to be involved in identifying a global cause and effect based on the analysis of the results of an online user study with 44 participants, who used both sequential and non-sequential graph layouts. In summary, the results show that participants show geodesic-path tendencies when selecting causes and derived effects, and that context matters, i.e., participant’s own beliefs, experiences and knowledge might influence graph interpretation.

Place, publisher, year, edition, pages
Springer, 2017. p. 22-34
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 10273
Keywords [en]
cause and effect, strenght and significance, graph visualization, user study
National Category
Computer and Information Sciences
Research subject
Skövde Artificial Intelligence Lab (SAIL); INF301 Data Science
Identifiers
URN: urn:nbn:se:his:diva-14191DOI: 10.1007/978-3-319-58521-5_2ISI: 000454445900002Scopus ID: 2-s2.0-85025150109ISBN: 978-3-319-58520-8 (print)ISBN: 978-3-319-58521-5 (electronic)OAI: oai:DiVA.org:his-14191DiVA, id: diva2:1146281
Conference
Thematic track on Human Interface and the Management of Information, held as part of the 19th International Conference on Human–Computer Interaction, HCI International 2017, Vancouver, Canada, 9 July 2017 through 14 July 2017
Projects
BIDAF
Funder
Knowledge FoundationAvailable from: 2017-10-02 Created: 2017-10-02 Last updated: 2020-06-18Bibliographically approved

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Bae, JuheeHelldin, ToveRiveiro, Maria

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