IDeaS 2019 Workshop: Interpretive Approaches to Data Science in Management Research
Alberta School of Business Edmonton AB T6G 2R6 Canada
The IDeaS group is an emerging working group, coming out of a collaboration between the University of Alberta and University of British Columbia. We are pleased to offer a two-day intensive workshop that provides management doctoral students and faculty members working in the areas of data science, data analysis, Big Data, and artificial intelligence an opportunity to discuss and advance their ongoing research. Distinctively, this event will draw together three interrelated topics that are more normally studied in separate scholarly communities:
- The reflexive and theoretically informed use of new data analytic techniques in the social sciences that leverage sophisticated algorithms such as topic modeling, natural language processing, and other forms of machine learning.
- The everyday work of data analysts in organizations - how they construct knowledge practices, and the epistemic infrastructures of organizations; both as an interesting ethnographic and qualitative topic in its own right, and as a means of encouraging our own reflexivity.
- The societal, social, and cultural transformations attending the rise of data and analytics – including changing forms and interpretations of privacy and governmentality – to which social scientists should be able to speak.
This event aims to bring together scholars interested in setting an agenda for studying and applying analytics in management research. The workshop will facilitate four activities:
- Fostering the development of cutting edge research skills among scholars interested in ethnographic/interview-based studies of technology and those applying computational methods in their research
- Allowing participants to advance their ongoing research through intense, focused feedback
- Exploring potential future directions for this research agenda
- Providing a forum for participants to network and share ideas about cutting edge research involving analytics
- Vern Glaser
- Tim Hannigan
- Dev Jennings
- Jennifer Sloan
- Chris Steele
- Rodrigo Valadao