Digital Trace Data Research in Information Systems: Opportunities and Challenges

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

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer 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
OriginalsprogEngelsk
TitelECIS 2023 Proceedings
Antal sider8
ForlagAssociation for Information Systems. AIS Electronic Library (AISeL)
Publikationsdato2023
StatusUdgivet - 2023
BegivenhedThe 31st European Conference on Information Systems. ECIS 2023 - University of Agder, Campus Kristiansand, Kristiansand, Norge
Varighed: 11 jun. 202316 jun. 2023
Konferencens nummer: 31
https://ecis2023.no/

Konference

KonferenceThe 31st European Conference on Information Systems. ECIS 2023
Nummer31
LokationUniversity of Agder, Campus Kristiansand
Land/OmrådeNorge
ByKristiansand
Periode11/06/202316/06/2023
Internetadresse
NavnProceedings of the European Conference on Information Systems
ISSN0000-0034

Emneord

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

Citationsformater