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At SAGE Campus we like to find out from our course instructors which computational methods they’re using for their own research. We caught up with Jon Slapin, course instructor on Fundamentals of Quantitative Text Analysis for Social Scientists and asked him a few questions.     


What inspired you to do what you do?

While much of my research today involves working with and analysing data, I became interested in my line of work through my interest in politics, and European politics in particular. As a 15 year-old high school student from New Jersey, I spent a few weeks in Germany on a summer abroad program. When we travelled from Germany to Austria for a weekend trip, we needed to cross a border and show our passports. Only a few years later when I returned as part of a university exchange program, the borders had vanished. I wanted to understand why. How was that European countries decided to integrate their politics to a point that borders disappeared?  These questions led me to study to political science, and while doing my PhD, I quickly realized that I would need some fairly sophisticated statistical and data analytic tools to answer the types of questions that interested me.


What advice would you give to someone new to data science?

Keep practicing and do something every day. Learning data analytical tools (including statistics, coding, and other tools) is like learning several new foreign languages at once. Getting a grasp on them takes time and requires repetition. But the more you use these tools the better you become at using them.



Which tools provide the most value to researchers?

Gaining reasonable proficiency in the R statistical language is probably the most valuable thing a budding data scientist can do. R is an amazingly powerful tool for statistical analyses, creating graphics, and managing data. Moreover, it’s free! Can’t beat that for value.


What data science skills should researchers be building on to boost their research?

Something that I wish I were better at myself is managing version control and workflow. Managing versions of code or manuscripts is even more important when working with collaborators in larger teams. Learning use online platforms like Github could be quite valuable.


Find out more about Jon's course - Fundamentals of Quantitative Text Analysis for Social Scientists

Want to hear more from Jon? Take a look at his other blog posts: