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Communication analysis


Our understanding of distributed decision making in professional teams and their performance comes in part from studies in which researchers gather and process information about the communications and actions of teams. In many cases, the data sets available for analysis are large, unwieldy and require methods for exploratory and dynamic management of data. In this project, we report the results of interviewing researchers on their work process when conducting such analyses and their use of support tools in this process. Our aim with the study was to gain an understanding of their workflow when studying distributed decision making in teams, and specifically how automated pattern extraction tools could be of use in their work. Based on an analysis of the interviews, we elicited three issues of concern related to the use of support tools in analysis: focusing on a subset of data to study, drawing conclusions from data and understanding tool limitations. Together, these three issues point to two observations regarding tool use that are of specific relevance to the design of intelligent support tools based on pattern extraction: open-endedness and transparency.


[1] Ola Leifler and Henrik Eriksson. Text-based analysis for command and control researchers - the workflow visualizer approach. Cognition, Technology & Work, 2011.
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Keywords: decision making, text clustering
[2] Ola Leifler and Henrik Eriksson. Analysis tools in the study of distributed decision-making: a meta-study of command and control research. Cognition, Technology & Work, 2011.
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Keywords: text analysis, command and control, decision making
[3] Ola Leifler and Henrik Eriksson. Message classification as a basis for studying command and control communications - an evaluation of machine learning approaches. Journal of Intelligent Information Systems, 2011.
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Keywords: machine learning, text clustering

Page responsible: Henrik Eriksson
Last updated: 2018-01-28