This is a two part series that will look at how social media data can be downloaded and analyzed spatially to understand urban patterns in places where more traditional data sets are hard to come by. We will be focusing on Shenzhen, a Chinese city that has gone through rapid urban development over the last 20 years. The work of both modules will be exhibited as part of the Shenzhen / Hong Kong Biennale. The first module (11.S946) will be led by Luc Anselin, a leader in Spatial Statistics. This module will focus on using spatial statistics to understand how “Big Data” data can be used to understand cities, using the geo-located social media data download for Shenzhen as an example. The second module (11.S947) will be led by Sarah Williams, a leader in data visualization. This module will take the analysis from module # 1 and transform them into compelling visualizations. The best student visualizations will be included in the Shenzhen /Hong Kong Biennale.
Big Data, is it new? Geographers have been working with what many would consider Big Data and applying methods to analyze those big data sets for years. There is much to learn from the analysis strategies developed. However, these methods have not been widely applied for analysis at the scale of the city. The work has largely focused on regional spatial patterns. How can these complex spatial analysis strategizes be applied to the micro-scale geographies of dynamics urban neighborhoods. This hands-on workshop will work with geo-tagged social media data downloaded for Shenzhen. Students will learn Spatial Statistics methodologies and use the Geoda software. The results of the Spatial Analytics performed in this class will be visualized in the partner course, “Visualizing Shenzhen’s Social Media to Understand City Dynamics”. Students who are interested in visualization can take the partnering course, but it is not a requirement.
Pre-Reqs : Knowledge of GIS, either 11.205 or previous work in GIS
Class meets September 4th through October 16th