Angus, Rintel, & Wiles (2013, p.265) note that “[s]ocial research methodology that uses visual-first analytic methods is still in its infancy”. We aim to further this field by developing novel social research methodologies that employ empirically built visuals, providing new insights on qualitative (text-based) data while minimizing observer bias. Our methodologies are made available as soon as possible to the research community and broader public to allow for continual application and improvement of the methods and techniques involved, hopefully leading to new methodologies that best capture and synthesize ideas and innovations from text-based data.
This webpage is currently under development, and active links and resources will be added as the page develops.
Newell-Dale Conversation Modelling Technique
The Newell-Dale Conversation Modeling Technique (NDCMT) was designed for in-depth analysis of e-Dialogue conversations, using an empirical methodology to minimize observer bias. NDCMT captures ideas that emerge through discussion, identifies connections between ideas and broader themes, and provides insight on the underlying patterns of discussion. NDCMT contributes to work done on social research methodologies that analyze dialogue by providing a new way of capturing the richness of conversation outcomes and processes and thus improving synthesis of innovations emerging through discourse.
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Angus, D., Rintel, S., & Wiles, J. (2013). Making sense of big text: a visual-first approach for analysing text data using Leximancer and Discursis. International Journal of Social Research Methodology, 16(3).