Abstract
Large-scale qualitative-temporal research faces significant data management and analysis challenges due to the size and the textual and temporal nature of the datasets. We propose a systematic methodology that employs visual exploration to produce a purposive sample of a much larger collection of data, followed by a combination of thematic analysis and visualization. This method allows for the preservation of the whole, producing thematic timelines that can be used to elucidate a narrative of incidents or issues as they unfold. We present a step-by-step guide for this methodology and a comprehensive example from the domain of social media analysis to illustrate how it can be used to reveal interesting temporal patterns among tweets relevant to a noteworthy incident. The approach is useful in sport management, particularly for research related to fan behavior, critical incident management, and media framing.
Published Version
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