Doing research is one of my happy places from research design to execution. I am always spending time reviewing literature to stay current in my research interests and to contribute to my research design and methods. My research interests are Computational Social Science, Data Science, E-Government, Machine Learning, Public Administration, and Public Policy. I am heavily influenced by STEM as I work in a STEM environment which contributes to my research interests. One of my other happy places is when I am programming in R, specifically RStudio, and it is part of the foundation of my research approach. Data Science and Machine Learning are fascinating disciplines and their application can be adapted by other disciplines such as the Social Sciences. There is a global human resource challenge in finding individuals from various domains that do programming; statistics; data wrangling to a tidy format in preparation for data analysis and data visualization; and employ Machine Learning algorithms.
I am integrating Data Science and Machine Learning into my research and research methods as part of my long-term research approach.
When you spend time reviewing literature, you discover new methods, disciplines, and buzz words. I was reviewing literature on Computational Social Science and it represents my long-term research approach. Computational Social Science is employing computational methods such as Data Science and Machine Learning to inform and solve complex problems in Social Science. Public Administration and Public Policy are subdisciplines of Social Science. Computational Social Science can be executed when Social Scientists and Computer Scientists collaborate and when a Social Scientist is skilled to employ computational methods.
My long-term research focus is how data science and machine learning algorithms can inform and solve complex problems in public administration, public policy, and other sub-disciplines of Social Science.