What Does It Take To See Gentrification Before It Happens? | NPR

Big data is a shorthand term for the insane amounts of information being generated by human beings in our digital world. From cellphones to credit card transactions to social media, we are all leaving digital contrails of almost all of our activity in the world. Learning how to harvest and analyze these digital traces en masse holds the promise of allowing data scientists to see how societies operate at a resolution that was simply impossible before. And seeing hidden patterns in gentrification may be exactly the kind of task big data and data science are best at.

So what does it take to see gentrification before it happens? The most obvious indicator is housing prices. Cities have always done a pretty good job of keeping track of property sales. That is why those records have, for many decades, been the primary data set for studies of neighborhood change. But big data has already swept through the housing price field, as apps like Zillow and Trulia allow anyone access to real estate information going back years. Using a data science technique called machine learning, computers can analyze patterns in these real estate records and extract future trends — allowing companies to try to predict what your house will be worth next year.

But even if it works, this kind of “predictive analytics” for housing prices is too blunt an instrument to predict which neighborhoods might gentrify. To really develop an early warning system, data scientists need to go deeper into human behavior. Going deeper, however, means getting new kinds of data.

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What Does It Take To See Gentrification Before It Happens? : 13.7: Cosmos And Culture : NPR.