Researchers Build Model for Predicting Gentrification
According to an article by Nathan Collins, data scientists from the University of Cambridge think they're found a way to predict gentrification, using data collected on Twitter and Foursquare. According to the model, the most likely places to gentrify attract the most socially diverse crowds.
The article details the process of building the data archive that informed the model, especially with regard to attention paid the differences between geographic networks and social networks.
Another important metric contributing to the research: the United Kingdom's Index of Multiple Deprivation, which, according to Collins, "takes into account income, education, environmental factors such as air quality, and more to quantify the socioeconomic state of affairs in localities across the U.K., including each of London’s 32 boroughs." Collins explains in more detail how that data keyed into the research findings on how social diversity predicts gentrification.