Abstract
Digital trace data research is an emerging paradigm in Information Systems (IS). Whether for theory development or theory testing, IS scholars increasingly draw on data that are generated as actors use information technology. Because they are ‘digital’ in nature, these data are particularly suitable for computational analysis, i.e. analysis with the aid of algorithms. In turn, this opens up new possibilities for data analysis, such as process mining, text mining, and network analysis. At the same time, the increasing use of digital trace data for research purposes also raises questions and potential issues that the research community needs to address. For example, one key question is what constitutes a valid contribution to the body of knowledge and how digital trace data research influences our collective identity as a field? In this panel, we will discuss opportunities and challenges associated with digital trace data research. Reflecting on the panelists’ and the audience’s experience, we will point to strategies to mitigate common pitfalls and outline promising research avenues.
Recommended Citation
Wurm, Bastian; Wessel, Michael; Tremblay, Monica Chiarini; Avital, Michel; Hukal, Philipp; and Junglas, Iris, "DIGITAL TRACE DATA RESEARCH IN INFORMATION SYSTEMS: OPPORTUNITIES AND CHALLENGES" (2023). ECIS 2023 Panels. 1.
https://aisel.aisnet.org/ecis2023_panels/1