Social Media Research with Word Association Thematic Analysis
Brand new course for 2021!
Date: 9 June 2021
Time: 9:30am - 4pm
Instructor: Mike Thelwall
This course is a practical walk-through of the word association thematic analysis (WATA) method to investigate sets of social media (or other short) texts. This method is suitable for identifying gender, national, time, or topic differences in a set of 10,000+ tweets or other short texts. The method finds word-level differences that are then translated into different themes. The procedure starts with using the free software Mozdeh to gather or import the texts, then uses Mozdeh to produce lists of words occurring more in one subset of the texts than another (e.g., male vs. female vs. nonbinary; UK vs. USA; recent vs. old; topic 1 vs. topic 2; topic 1 vs the rest). Next, a two-stage manual thematic analysis is applied to identify themes within the words found. The result is a set of themes characterising substantial differences between the texts. The course goes through all these stages with a small set of texts.
In this course, participants will learn:
- how to apply word association thematic analysis to a set of social media texts
- how to use the word association thematic analysis functions in the free software Mozdeh.
To enrol in this intermediate course, participants must have either:
- attended the introductory course Social Media Data Analysis; or
- experience of a social media research project.
You will also need:
- a Windows computer
- a Twitter account and familiarity with using Twitter
- basic knowledge of statistics.
If you have any questions about the course prerequisites, please get in touch.
Thelwall, M. (2021). Word association thematic analysis: A social media text exploration strategy. San Rafael, CA: Morgan & Claypool. https://doi.org/10.2200/S01071ED1V01Y202012ICR072
Thelwall, M., Makita, M., Mas-Bleda, A., & Stuart, E. (2021). “My ADHD hellbrain”: A Twitter data science perspective on a behavioural disorder. Journal of Data and Information Science, 6(1). https://doi.org/10.2478/jdis-2021-0007
About the instructor
Mike Thelwall is a professor of Data Science and head of the Statistical Cybermetrics Research Group at the University of Wolverhampton. He develops and applies software and methods to analyse social media texts.