AS PhD data

In this project, I will analyze large publicly available datasets using machine learning to reveal new associations that can help refine existing theories or develop new theories in the social and management sciences. In the first project, I discuss some of the limitations of traditional statistical approaches and demonstrate how we can solve them using machine learning. In the second project, I demonstrate how machine learning can sieve through a large amount of data to identify patterns. In the third project, I document that machine learning models can be used to generate hypotheses that are subsequently validated by traditional methods (e.g., correlational and experimental studies). Machine learning models take a long time to build, requiring considerable software writing. However, these models are reusable. In the fourth project, I demonstrate how a machine learning model built in the third project can be reused for a different topic.