“Quantitative analysis of social data has an alluring exactness to it. It allows us to estimate the average number of minutes of YouTube videos watched to the millisecond, and in doing so it gives us the aura of true scientists. But the advantage of quantitative analyses lies not in the ability to derive precise three-decimal point estimates; rather, quantitative methods shine because they allow us to communicate methodological goals, assumptions, and results in a (hopefully) common, compact, and precise mathematical language. It is this language that helps clarify exactly what researchers are doing with their data and why.”
A lot of industry “data science” is moronic, which is to say not clear about assumptions or about what is and isn’t possible with the estimates. Leading case: Models are treated as causal when they are not. Antidotes to that kind of thinking are great. Hopefully this can be one of them. I’ll keep looking at it.