Koelbel - 402P
My research interest is in text mining user generated contents (UGC) such as tweets and user postings during disaster situations to identify patterns in both form and content. I am also interested in text mining cultural differences. For example, a recent project develops a text-analytic method that examine user posted reviews and identify factors people in different cultural groups perceive as important when making their travel choices. A related thread of his research uses text analytic methods to study how a given concept might differ across organizational and national cultures. For example, it develops a method to identify how a concept such as cell phone or vacation might differ across different generational groups (e.g. millennials vs. baby boomers) or national cultures.
My past research has focused on process knowledge as captured in the form of process model and ontology. This effort led to successful results such as the Process Interchange Format, which has been incorporated into the National Institute of Standards and Technology Process Specification Language. The inter-nomological network project, partially funded by NSF, examines some of these questions in the context of interdisciplinary research.
My articles have been published in MIS Quarterly, Management Science, Human Computer Interactions, among others.
Ph.D. Computer Science, Massachusetts Institute of Technology
M.Phil. History and Philosophy of Science, University of Cambridge, England
M.A. Psychology and Social Relations, Harvard University