TY - JOUR
T1 - Developing theory through integrating human and machine pattern recognition
AU - Lindberg, Aron
N1 - Publisher Copyright:
© 2020 by the Association for Information Systems.
PY - 2020
Y1 - 2020
N2 - New forms of digital trace data are becoming ubiquitous. Traditional methods of qualitative research that aim at developing theory, however, are often overwhelmed by the sheer volume of such data. To remedy this situation, qualitative researchers can engage not only with digital traces, but also with computational tools that are increasingly able to model digital trace data in ways that support the process of developing theory. To facilitate such research, this paper crafts a research design framework based on the philosophical tradition of pragmatism, which provides intellectual tools for dealing with multifaceted digital trace data, and offers an abductive analysis approach suitable for leveraging both human and machine pattern recognition. This framework provides opportunities for researchers to engage with digital traces and computational tools in a way that is sensitive to qualitative researchers’ concerns about theory development. The paper concludes by showing how this framework puts human imaginative capacities at the center of the push for qualitative researchers to engage with computational tools and digital traces.
AB - New forms of digital trace data are becoming ubiquitous. Traditional methods of qualitative research that aim at developing theory, however, are often overwhelmed by the sheer volume of such data. To remedy this situation, qualitative researchers can engage not only with digital traces, but also with computational tools that are increasingly able to model digital trace data in ways that support the process of developing theory. To facilitate such research, this paper crafts a research design framework based on the philosophical tradition of pragmatism, which provides intellectual tools for dealing with multifaceted digital trace data, and offers an abductive analysis approach suitable for leveraging both human and machine pattern recognition. This framework provides opportunities for researchers to engage with digital traces and computational tools in a way that is sensitive to qualitative researchers’ concerns about theory development. The paper concludes by showing how this framework puts human imaginative capacities at the center of the push for qualitative researchers to engage with computational tools and digital traces.
KW - Abduction
KW - Computational Tools
KW - Digital Trace Data
KW - Human Pattern Recognition
KW - Machine Pattern Recognition
KW - Pragmatism
KW - Theory Development
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U2 - 10.17705/1jais.00593
DO - 10.17705/1jais.00593
M3 - Article
AN - SCOPUS:85079496898
SN - 1558-3457
VL - 21
SP - 90
EP - 116
JO - Journal of the Association for Information Systems
JF - Journal of the Association for Information Systems
IS - 1
ER -