Social Media and the Spread of Mass Psychogenic Illness
Project Description
This project examines the social contagion of mental health symptoms in the age of social media and places it in historical context. Mass psychogenic illness, also known as mass hysteria, involves the spread of illness symptoms in a population through social means rather than through an infectious agent. Contemporary examples of rapid increases in mental health symptoms among social media communities that have been characterized by experts as mass psychogenic illness are (1) Tourette Syndrome, (2) dissociative identity (multiple personality) disorder, (3) eating disorders, and (4) rapid onset gender dysphoria. We will investigate (1) whether such cases do indeed qualify as mass psychogenic illnesses and, if so, (2) the similarities and differences between modern mass psychogenic illnesses and those of a previous era prior to social media. Given that there are several streams of ongoing research, the specific topic can be matched to the interests of the applicant.
Supervisor
HENDRY, David James
Quota
1
Course type
UROP1100
UROP2100
UROP3100
UROP4100
Applicant's Roles
The applicant’s role may include conducting literature reviews, searching for, collecting, and cleaning quantitative and qualitative data from the web, developing tools for the systematic collection of social media data, data analysis, and assisting with the development of new research questions. No specialized prior knowledge is required, and the specific tasks can be matched with the applicant’s skill level and interests. Students with no prior knowledge of programming or software for statistical analysis are encouraged to learn the basics of at least one software platform for some aspect of the project (e.g., R for statistical analysis, Python for web scraping and API interaction).
Applicant's Learning Objectives
Students will learn to formulate research questions, conduct literature reviews, perform qualitative and quantitative content analysis of social media data, and perform basic web scraping routines. The project will give students hands-on experience with various aspects of projects analyzing large corpuses of social media data.
Complexity of the project
Moderate