Digital Trace Data Research in Information Systems: Opportunities and Challenges

Bastian Wurm, Michael Wessel, Monica Chiarini Tremblay, Michel Avital, Philipp Hukal, Iris Junglas

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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
Original languageEnglish
Title of host publicationECIS 2023 Proceedings
Number of pages8
PublisherAssociation for Information Systems. AIS Electronic Library (AISeL)
Publication date2023
Publication statusPublished - 2023
EventThe 31st European Conference on Information Systems. ECIS 2023 - University of Agder, Campus Kristiansand, Kristiansand, Norway
Duration: 11 Jun 202316 Jun 2023
Conference number: 31
https://ecis2023.no/

Conference

ConferenceThe 31st European Conference on Information Systems. ECIS 2023
Number31
LocationUniversity of Agder, Campus Kristiansand
Country/TerritoryNorway
CityKristiansand
Period11/06/202316/06/2023
Internet address
SeriesProceedings of the European Conference on Information Systems
ISSN0000-0034

Keywords

  • Digital trace data
  • Computational social science
  • Computational theory development
  • Research methods

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