Z604/Z672 Comic Books and Their Readers
Digital and Empirical Methods for Studying Readership and Fandom
Spring 2024
12:40 - 15:15 Wednesday, Sycamore Hall (SY) 103
Instructor: Associate Professor John A. Walsh, jawalsh@indiana.edu.
Office Hours: Schedule at https://fantastical.app/jawalsh-r1Wz/office-hours.
Associate Instructor: Alex Wingate, alewinga@iu.edu
Office Hours: Thursdays, 1:30pm-2:45pm, and by appointment (click Zoom link in Alex’s profile)
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Summary
This week we explore fandom on social media and tools for analyzing social media data.
Weekly Learning Objectives
- illustrate social media research with examples from various domains.
- list example topics that may be analyzed through social media data.
- list, explain, and discuss pros and cons of three methods for obtaining social media data.
- use one or more methods discussed in class to obtain comics- or fandom-related social media data.
Before class: Readings, resources, and tasks
Weekly learning objectives
- Dill-Shackleford, K. E., Hopper-Losenicky, K., Vinney, C., Swain, L. F., & Hogg, J. L. (2015). - Mad Men fans speak via social media: What fan voices reveal about the social construction of reality via dramatic fiction. Journal of Fandom Studies, 3(2), 151-170. <Retrieved from https://proxyiub.uits.iu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=cms&AN=103531154&site=ehost-live&scope=site>
- Lowe, J. S. A. (2017). We’ll always have purgatory: Fan spaces in social media. Journal of Fandom Studies, 5(2), 175-192. <Retrieved from https://proxyiub.uits.iu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=cms&AN=126397445&site=ehost-live&scope=site>
- Web Scraping with Python. Requires some basic knowledge of Python. If you don’t know Python, see: Learning Python
In class
- Mark Bell, comics creator (See examples of Mark’s work in our comics folder on OneDrive)
- Discussion