Several months ago, I wrote about a presentation on spam in educational Twitter research that I prepared with my colleagues Jeff Carpenter, Matt Koehler, and Bret Staudt Willet. Since that presentation, we’ve been hard at work continuing this project, and I’m pleased to announce that Spam and educators’ Twitter use: Methodological challenges and considerations is now available “online first” through TechTrends. At the time of posting, the article can be read without a paywall here.
For your reference, here is the abstract for the article:
Twitter and other social media have assumed important places in many educators’ professional lives by hosting spaces where new kinds of collegial interactions can occur. However, such spaces can also attract unwelcome Twitter traffic that complicates researchers’ attempts to explore and understand educators’ professional social media experiences. In this article, we define various kinds of spam that we have identified in our research on educators’ uses of Twitter. After providing an overview of the concept of spam, we evaluate the advantages and disadvantages of different approaches to addressing the presence of spam in educator-focused Twitter spaces. Then we suggest practical, holistic metrics that can be employed to help identify spam. Through secondary analyses of our past research, we describe the use of such metrics to identify and deal with spam in three specific cases. Finally, we discuss implications of spam and these suggested methods for teacher educators, instructional designers and educational technology researchers.
I’m very happy to have the chance to contribute more to the literature on social media research methods in educational technology. The five years or so that I’ve spent doing Twitter research in educational (and, increasingly, other) contexts have been full of learning opportunities that I’m eager to share with the rest of the ed tech research community. As Royce Kimmons and George Veletsianos have written with regard to “Public Internet Data Mining Methods in Instructional Design, Educational Technology, and Online Learning Research”,
The first challenge and largest barrier to entry for most education researchers who might have an interest in public internet data mining is that collecting, cleaning, organizing, and analyzing these data at any scale relies upon various technical skills that are interdisciplinary (at best) or not taught at all in most education research programs. (p. 496)
In short, ed tech researchers’ access to innovative research methods for studying phenomena of interest is increasing, but ed tech researchers are typically not trained in these methods. My hope in publishing papers like this one on spam is that my colleagues and I can share some of the lessons we’ve learned with those who are figuring out how to do this on their own (just like we did). Including rich methodological discussions in our literature can help us both embrace more fully and—more importantly—employ more critically the innovative methods that are now at our disposal.