Leveraging Influencer Groups to Examine Learning Networks on Twitter

Abstract

Our study builds on theories emphasizing connectivity for learning on social media to study learning networks on Twitter (e.g., Haythornthwaite, 2019; Siemens, 2005). Considering the nature of power law distribution on social media (Yoshida, 2021), we focus on a group of influencers from the Non-Fungible Token (NFT) community to uncover online learning networks and their emergent practices. By employing an exploratory Social Network Analysis (Nooraie et al., 2020) and qualitative analysis, we examine the way in which influencers form learning relations through conversational interactions and content, and the modalities and discursive strategies used in their tweets. We find that influencers built a strong learning network through sustained interactions and content relations among themselves and with a wide community outreach. This analysis contributes to the way that learning networks are analyzed and found on Twitter.