Home // HUSO 2019, The Fifth International Conference on Human and Social Analytics // View article
Authors:
Thomas McDermott
Molly Nadolski
Keywords: knowledge management; complex adaptive systems; data visualization; conceptual modeling; leadership
Abstract:
We present a framework and sample case study linking knowledge visualization forms with visualization of human and social data analytics. This involves integration of qualitative methods to identify and connect conceptual models with computational social science approaches for data analytics. The framework addresses two challenges: explicitly linking conceptual knowledge visualization to data analytic tools and using that linkage to explore complexity in social situations. In social or organizational change management strategies, combining new data and knowledge is critical for decision making. When the situation is complex, data must be placed in a knowledge framework to build team learning and to create new mental models for strategic change. As situational complexity increases, the role of knowledge transfer in team social networks becomes more critical, and the ability to visualize knowledge (as opposed to information) becomes paramount to insight and effective decision making. We demonstrate a framework that is derived from theories in the systems thinking and complexity thinking domains, which is then linked to how leaders and managers visualize and communicate data, information, and knowledge. A case study based on Russia’s multi-domain influence in the country of Moldova is used to demonstrate explicit linkage between knowledge visualization forms and social data analytics.
Pages: 37 to 42
Copyright: Copyright (c) IARIA, 2019
Publication date: June 30, 2019
Published in: conference
ISSN: 2519-8351
ISBN: 978-1-61208-725-2
Location: Rome, Italy
Dates: from June 30, 2019 to July 4, 2019