Spam and Educators’ Twitter Use: Methodological Challenges and Considerations
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.
KeywordsHashtags Professional community Professional learning Research methods Spam Social media Twitter
Compliance with Ethical Standards
Disclosure of Potential Conflicts of Interest
The authors declare that they have no conflict of interest.
Research Involving Human Participants and/or Animals
This article contains no studies with animals performed by the authors. All actions performed in studies involving human participants were conducted in accordance with the ethical standards of the relevant institutional review board, and also with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
This paper conducts secondary analysis of data collected during two earlier studies (Carpenter et al. 2018; Staudt Willet 2019). Those studies, as well as this current one, included only publicly available data from the social media platform Twitter that were collected unobtrusively. The data are described only in aggregate; we do not point to individual users in any identifiable way and generally focus on behavior trends among a corpus of several thousand participants on social media. As such, informed consent was deemed unnecessary by the respective Institutional Review Boards.
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