Abductive theorizing: Using big data and machine learning

Contributed Talk | Day 3 | 8:30 am | 40 Minute Duration | Grand Gallery A
  • Omar Malik
    Heidelberg University School of Business, Computer Science, and Information Technology Associate Professor of Management

Abductive theorizing: Using big data and machine learning

Contributed Talk | Day 3 | 8:30 am | 40 Minute Duration | Grand Gallery A

This research presents a framework for applying big data and Machine Learning (ML) methods to the theory development process in the social sciences. I use the elements of theory: What? How? Why? Who? When? and Where? to illustrate how big data conceptualized along an axis of high to low integrity data can be used for nascent and intermediate theory development. I also apply the elements of theory development to three classes of ML methods: Supervised, Semi-supervised and unsupervised learning.