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Code to build the website tutorials for the Social Life of Neighborhoods course offered through Stanford's Sociology department in the spring quarter of 2021.

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francine-stephens/social-life-of-neighborhoods

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Data Preparation & Mapping Tutorials for the Social Life of Neighborhoods Course

The Social Life of Neighborhoods was a course offered through Stanford's Sociology Department in the spring of 2021. The underlying goal of the course is to mount a quarter long intellectual investigation of a neighborhood and the various processes that structure its “social life”— that is, the way it developed historically, reproduces itself on a daily basis, and is subjectively experienced by various individuals and groups. View the course syllabus to see a complete description of the course and all of the assignments.

This repository contains the code used to create each tutorial for the course assignments. The website includes a main landing page to orient the reader and seven distinct chapters, which are tutorials that guide the students through the steps required to create maps and other visuals for the course assignments. The tutorials introduce students to the fundamentals of handling spatial data, creating interactive web-maps using ESRI ArcGIS Online, and compiling their web-maps and other types of multimedia into a data-storytelling platform. A table of contents for each of the tutorial pages is listed in the table below. The names of the rmarkdown files in the main-directory correspond to the chapter number and tutorial name.

Chapter Tutorial Name
2 Using Social Explorer
3 Intro to ArcGIS Online
4 Geocoding
5 Mapping Crime Data
6 Mapping Segregation
7 Mapping Gentrification
8 ESRI Story Maps

In the tutorials, the steps are written out and visually demonstrated with images and GIFs. The visual content in the tutorials can be found in the images sub-directory. There are also tables featured in the tutorials to guide students to particular geographies or key data to use in their write-up. The information in these tables can be found in the csv files that are included in the main directory.

View the website and all of the tutorial content here.