For the next four months of the CHI Fellowship, I will be building my project, provisionally titled Mapping Consumers in the Black South African Press.
As I’ve discussed in previous posts, I’m interested in what we can learn about consumer culture — both the consumption that companies wanted to promote, and the individual values of consumers themselves — through testimonial advertisements in early twentieth-century South Africa.
This project will create maps of data that I have already collected, and will continue to collect, from testimonial advertisements and write-in competitions in newspapers. I have already collected data from Umlindi we Nyanga (1934-1943). I will also collect data from Bantu World, (founded in 1932) the black newspaper with the largest circulation in the mid-twentieth century. I will collect data from the World from 1932 to 1953 (the end of the paper’s first editorship by RV Selope-Thema).
The outcome will be a website. The main feature of the website will be an interactive map. The map will display pins marking the location of consumers who appear in testimonials. It will allow users to interact with the data in terms of chronology, geography, and other factors (gender of the writer if stated, what language the advertisement is in). The website will also have contextual short essays about each of the newspapers.
Functionality & Technology
Functionality: The home page will contain a description of the project. The navigation bar will link to three other pages:
- The interactive map
- A description of my workflow and data collection process, as well as my actual data files (.csv files)
- About and contact page
Technology: The website will be built using a Bootstrap template. The main technology on the website will be the map. I will build the map with Bootleaf. At the moment, my working plan is to use a Leaflet map tileset, although if I can find an appropriate historical map I will create my own tileset.
My .csv data files will be converted into GeoJSON files.I will create a different dataset for each newspaper that I collect from. Users of the map will then be able to choose one or both datasets to display. The datasets themselves can also be filtered for different variables (date, product).
Right now, I’ve finished collecting and organizing my data, and now I’m at work tinkering with the Bootleaf code to make it meet my needs.