Mapping Amman’s Social Media Landscape

This project includes mapping Amman’s social media landscape and exploring how Amman’s citizens imagine their place in the country’s neoliberal investment project. 

Project Lead:

Betty S. Anderson, Associate Professor
History Department, College of Arts & Sciences
Director of the Institute for the Study of Muslim Societies and Civilizations (2015-17)

Detailed Project Description:

I am currently undertaking a multi-pronged project examining the physical, economic, and social changes that have come to Amman, Jordan, in the 21st century. My primary interest is in studying how the government and citizenry are representing and defining their national, urban and class identities in the midst of a government-led neoliberal investment project. Even though Jordanian citizens have little input into the choices being made across the city, they are taking charge of how they use the new venues being created, ranging from new private educational institutions, to new jobs in the private sector, to new housing and transportation opportunities, to new means for advertising their choices on social media. The changes to Amman’s city-scape parallel those taking place across the region so Amman also serves as a useful case study for a globalizing Middle East.

Much small-scale investment has gone into new entertainment zones throughout the city such as Rainbow Street and Jabal Webdeih and the result has been the proliferation of new cafes and restaurants. For the first time, these locations have not only a real presence on the ground but one in the virtual world. Social media sites have enabled the owners and customers to present their own images of these newly built and reconfigured spaces, images that embrace the country’s neoliberal direction but which also highlight the differences in class, society and gender that these changes have wrought.

I have already done a manual study of Facebook, Yelp and Tip n’ Tag but the scope was too small to fully analyze how virtual Amman is being constructed by state leaders, owners of businesses and customers. I would like to have a student(s) obtain and code the comments and images on these sites as well as the Jordan Tourism Board if that is possible in a more comprehensive way to see how Jordanians are projecting their class, gender and consumption decisions out to the virtual world and how the state and business owners are generating customers. Amman contains approximately 30% foreigners (Syrian and Iraqi refugees, students studying Arabic, Arab Gulf investors, and international NGO workers, for example) who have access to social media sites as well so the depictions of Amman are not only for local consumption for foreigners as well. Is there a distinctive Jordanian social media presence or is it dominated by foreigners? Connected to this question: how useful can social media sites be in analyzing socio-economic changes to a society? I know of no other current research project in a Middle Eastern city that brings together social science questions with those made possible by computer coding.

Technical Components:

Provide assistance in the following topic areas: data analytics and data mining. 

I would like the students to scrape Facebook, Yelp, Tip ‘n Tag and the Jordan Tourism Board for images and descriptions posted by the state and business owners and the images and comments posted by the visitors to the real and virtual site. I would then like to work with the students to put together proper coding questions so that comparisons can be made between the images, slogans, brands, and narratives presented by the state and owners as advertising points and those showing how the visitors define the experience of using the real and virtual sites. I have done this kind of exercise manually through many different types of media but never through computer coding so this is an exciting new process for me.

Data Set(s):

The datasets required for the project should be scraped from Facebook, Yelp, Tip ‘n Tag and Jordanian Tourism Board sites.

Skill/Expertise Requirement(s):

1) Web scraping
2) Parsing html (to extract relevant data)