Methodology

Methodology Overview

Colors refracted through camera lens
Photo by Agence Olloweb on Unsplash

“Hashtag History” is a hybrid. As noted in the Literature Review, the analysis in this dissertation draws on the thematic fields of historical thinking as well as digital media and learning. The contexts of both Singaporean and American higher education frame the study and the participants, too, are diverse. The project’s Southeast Asian student participants hailed from many different racial and religious backgrounds and varied in gender, age, and experience of history. The class in which participants produced the data for this study was itself a mixture of online and in-person education practices. “The classroom” was not a single space, but rather an amalgamation of the physical space in which the class met and the online space in which ongoing discussions took place.

The methodologies of the project likewise reflect the trend toward hybridization in academia. In the digital humanities especially, disciplinary boundaries are porous and collaboration across disciplines is highly valued. Indeed, the use of sentiment analysis, word frequencies, and coding to create this project depended on the work of data scientists, sociologists, literary scholars, and historians.

The Methodology chapter of “Hashtag History” provides fuller details regarding the motivations for producing a digital dissertation, the setting of the study, and the methods used for data collection, compilation, and analysis methods. Briefly, the study took place in an undergraduate, world history course that is one of the required classes in the general education curriculum of the University at Buffalo, Singapore Institute of Management (UB-SIM) program in Singapore. I was the instructor for the course; the ethical dimensions of my dual role as researcher and educator are addressed in the section, “Study Contexts: Navigating Dual Roles as Educator & Researcher.” Students enrolled in my course comprised the participants. None of them were history majors and most had not taken a college-level history course prior to enrolling in my class. The public data they produced on Twitter and a class blog formed the dataset of 11,454 tweets and 74 blog posts (plus comments) utilized in the project.

Collection, compilation, and analysis of the data for “Hashtag History” involved digital humanities and qualitative methods. I employed web scraping as well as simple copying and pasting for the data collection. Compilation and cleaning took place in Google Sheets and R. I analyzed the data using text-mining strategies, including sentiment analysis and word frequencies. I also utilized the social sciences practice of coding, a form of identifying and labeling themes within a dataset. Finally, I employed close reading, a qualitative method concerned with the details of a text rather than overarching patterns.


Methodology Sections

Why Digital?

Study Contexts: Singapore, Private Education, and the Classroom

Participants

Data Collection

Data Compilation and Cleaning

Data Analysis