Best practice science communication research, practice, and evaluation often dictates the use of focus groups and interviews, and yet techniques for analysing data from such collection methods are rarely discussed. This paper reports on the use of Leximancer, an automated text-mining software tool, to examine and compare transcripts from two focus groups. Participants included in this study were part of an upstream engagement process aimed at getting leading Australian farmers together to form a cooperative group to disseminate scientific information about managing climate variability and climate change. Findings from the study show that while cursory automated qualitative analysis of transcripts may not serve as a substitute for in-depth analysis, they may be complementary.

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Public Communication of Science and Technology

 

Values and evaluation
Leximancer as a tool for analysing values in science communication transcripts

Melanie McKenzie   The University of Queensland and Econnect Communication

Best practice science communication research, practice, and evaluation often dictates the use of focus groups and interviews, and yet techniques for analysing data from such collection methods are rarely discussed. This paper reports on the use of Leximancer, an automated text-mining software tool, to examine and compare transcripts from two focus groups. Participants included in this study were part of an upstream engagement process aimed at getting leading Australian farmers together to form a cooperative group to disseminate scientific information about managing climate variability and climate change. Findings from the study show that while cursory automated qualitative analysis of transcripts may not serve as a substitute for in-depth analysis, they may be complementary.

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