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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
