On Thursday, 9 March from 12:00 to 13:30, in room 2636-U30, Assoc. Prof. Philipp Hukal from BI Norwegian Business School will be giving the following research presentation, followed by a Q&A session:

Induction of Rich Patterns from Digital Trace Data
 

Abstract: Ever more social interactions take place in digital technology environments where they produce vast amounts of digital trace data. Such data are not generated for the sake of research but are “found” and can thus relate to multiple phenomena of social interaction with digital technology simultaneously. Previous work has shown the potential of leveraging digital trace data as well as the need for reflection about the generation and interpretation of trace data for theorizing. To complement these efforts, we develop a model of inducting patterns from digital trace data by disaggregating the process into pattern focus (e.g., relational patterns, sequential patterns, or semantic patterns) and pattern fidelity (from low to high fidelity). Combine one or many pattern foci at varying levels of fidelity, allows researchers to leverage the multi-facetted characteristics of digital trace data and generate theory of emerging phenomena that exist on the intersection of structural, processual, or semantic aspects captured in digital traces. To illustrate the utility of these strategies for theorizing, we explain their implementation in archetypal and actual research designs. This paper contributes to the bourgeoning literature on computational methods and trace data analysis by providing a vocabulary as well as actionable guidance for building and assessing theory that draws from digital trace data.
 

Bio: Philipp Hukal is associate professor at the Department of Strategy and Entrepeneurship at BI Norwegian Business School. Before moving to Oslo, he was assistant professor at the Department of Digitalization at CBS. Philipp’s research is focused on digital innovation, platform strategy, open source software development and digital entrepreneurship. He works with computational and digital trace data methods in his research. He has published in journals such as MISQ and Information Systems Journal.