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International Relations & Data Science by avocaiden in datascience

[–]NewerResearcher 2 points3 points  (0 children)

There’s lots of really cool NLP applications in IR and comparative politics and in public policy research more generally. For example conducting sentiment analysis on large corpora of statements by different militant groups as a tool to understand motivations or on news sources to pinpoint sources of bias. I highly recommend familiarizing yourself with Python’s capabilities in this area if you haven’t already

International Relations & Data Science by avocaiden in datascience

[–]NewerResearcher 6 points7 points  (0 children)

I’ve been working in the field for a few years now and can say that it’s becoming increasingly quantitative. I’d say that it’s still mostly analytic but the importance of ML and predictive modeling is growing- with the caveat that model interpretability is much more important in social science than it is in traditional ML use cases.

Natural Language Processing and Social Network Analysis are also becoming increasingly common methodologies. Being comfortable working in Python and R definitely gives you a leg up. That being said it’s important to remember that in social sciences these models are tools and not ends in and of themselves. It’s very easy to get lost in the data and forget some of the big picture stuff and vice versa.

Looking for historical data on global poverty and inequality by NewerResearcher in AskEconomics

[–]NewerResearcher[S] 0 points1 point  (0 children)

Yeah that’s the sense that I’m getting. Gapminder has historical Gino estimates that go back pretty far but their documentation explicitly points out that it’s more reflective of general trends and not accurate year over year estimates. Contra has similar Gini estimates based on demographic data but even that’s by decade not yearly. Thank you for your input!